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Media Buying Briefing: Where media agencies will focus their energies this year

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Media Buying Briefing: Where media agencies will focus their energies this year

This year, 2023, might offer the murkiest start to a year in recent memory — it’s simply unclear where the brand marketing ecosystem (and all its participants) will end up financially, even though we know it’s not starting from a great place. 

Clients of media agencies remain uncertain about business conditions in 2023, and as a result have delayed decisions on marketing budgets, as well as where to spend those budgets given the huge increase in choices they have and decisions they have to make. At the end of last year, media agencies prognosticators predicted a decent year in media spend this year, in the higher single digits — but scaled back from larger increases they had called for earlier in 2022. 

In this column this week, we’d like to establish the biggest opportunities and challenges that lie ahead in 2023 for all media agencies, whether holding-company-owned or independent. But before we get to that, and speaking of holdco vs indie, what remains unchanged is the constant tussle between the two as the latter try to steal away a larger share. 

The indie argument for would-be clients is their nimbleness, their deep expertise in whatever discipline they specialize in, and their creative freedom to work with whoever and however they want. That has been an intoxicating pitch for major marketers like Nike, which landed all its North American media work with PMG last year.

But the holding companies, flush with new media channels and tactics they can bring to the table (commerce media, artificial intelligence/machine learning tools, and ESG/sustainability-focused investment), argue they offer the whole package in an era when more marketers want to reduce their roster of agencies working for them. 

“Our fundamental belief is, clients want fewer agencies solving much bigger problems,” said Jacki Kelley, CEO of Dentsu Americas and chief client officer for the parent company. “And we see this in the consolidation reviews that are going on — the desire to reduce complexity. So we have really retooled ourselves to deliver on that.”

Meanwhile, holdcos and indies alike are feeling the pinch of a newer generation of holding company in the form of Media.Monks, BrandTech Group or MediaPlus, which are leaner, faster networks with multi-national reach and modern tools.

And now, the opportunities/challenges media agencies will harness/face down this year: 

The influencer/creator market goes big time

It’s safe to say agencies are taking influencer marketing and the creator economy more seriously going forward. Experts explain that marketers and media agencies are beginning to experiment with new ways to leverage creator-driven content, from bots to micro influencers, in order to connect with audiences. Where there may have been more skepticism to influencer marketing in years past, now Fortune 500 companies and holding giants are investing in influencers and commerce strategies. The biggest potential obstacle ahead is that, with demand going up, some influencers will start charging more for their services. Global media spend in the influencer advertising segment is projected to reach $51 billion by 2027, increasing at an annual growth rate of 13.21% from 2022 to 2027, according to Statista.

Progress on data privacy

Agencies want a coherent national data privacy bill to be passed, as a way to bring order to the chaotic set of state-by-state rules, led by California’s updated CPRA. Because then, they’d at least know what they can and can’t do — and in a perfect world, bad actors that have collected data without securing proper consumer permission would be forced to either clean up their act or get shut down. Meantime, agencies are encouraging clients to find new ways to generate more privacy-compliant first-party data as historical forms of identifiable information (ie cookies) fade. The thirst for more data hasn’t eased a bit — quite the opposite, as agencies and marketers build more loyalty programs designed to build their databases while building deeper relationships with customers. Ad-tech and mar-tech firms keep coming up with newer platforms and SaaS products to make the process easier. Expect this trend to continue throughout the year.

Streaming keeps growing but problems persist

While traditional TV still accounts for more advertising spend, connected TV is closing in fast, with more premium inventory coming online at Netflix and Disney+. CTV will see some big changes ahead, like more potential consolidation across the supply chain, which could make mid-tier services and niche players good targets for acquisition. But it remains hard to track measurements on CTV, especially as services become more disjointed, which means media agencies will demand improved performance metrics from the medium in 2023. There’s also increasing interest in exploring interactive elements that engage audiences during the content, such as sports betting for live games or shopping for featured products in a show. 

On the audio streaming/podcasting front, experts anticipate steady growth as audio buying matures. With more quality content, use of smart speakers and a larger market (Spotify and YouTube introduced podcast features), these consumers are generally seen as a sticky audience. Marketers like podcasting for its precise audience targeting, dynamic messaging and outcome-based analytics. Plus, agencies will continue experimenting with different ad formats and content creators as platforms invest in this medium.

Social media hits harder times

The social media landscape is constantly shifting, with differing fortunes for big players and newcomers. Here’s what we know:

  • Some advertisers and brands have gradually shifted spending away from Facebook and Instagram and putting it into TikTok. While fast-growing, the Chinese-owned Bytedance app is increasingly coming under scrutiny by regulators citing national security and safety concerns, which could be a problem down the line.
  • Twitter remains unstable after acquisition by Tesla boss Elon Musk. Agencies have cautioned clients that Twitter is a “high risk” media buy, and it remains unclear whether Musk will continue to helm the company.
  • Snap may have seen some steady growth last year, but it also lost key advertising leadership to Netflix in September. As the company restructures, it may try to differentiate itself through augmented reality, which could offer a distinction from its social brethren for media buyers.
  • While BeReal appears to offer a refreshing new take, the social platform does not run on ads. Many are curious whether this French app can grow instead through subscriptions or premium content.

Will B2B stay hot?

Many agencies ramped up their business-to-business marketing prowess, as marketers grappled with the challenges of supply-chain issues and economic worries that forced them to ensure their business needs were as strong as possible. After all, it’s predicted to be a $30 billion marketplace in media spend, with digital channels sucking up close to half of those dollars this year. B2B marketing is another channel that’s been boosted by ad-tech advancements including account-based marketing and other SaaS-based tools that help otherwise disparate departments coordinate approaches so that supply and demand match. 

Expect to see more B2B marketing encroach into the consumer space, from sports to entertainment content as agencies target potential customers more effectively using these tools.

We will endeavor to cover all these topics and more throughout 2023. Thanks for reading! 

Color by numbers

WARC’s Marketer’s Toolkit 2023 highlighted the biggest digital commerce trends based on global data from 1,700 marketers. The big takeaway: Retail is now considered the fourth-largest advertising medium with an ad forecast of $121.9 billion globally this year (a 10.1% increase from 2022). For brands, agencies and partners, the three key areas to pay attention to are retail media networks, organizational readiness and social commerce. —AS

More stats:

  • Retail media ad spend has more than doubled from 2019 to 2022, surpassing audio, OOH and cinema, publishing and OTT/streaming. At this rate, WARC expects the retail media industry to become even more valuable to advertisers than linear TV by 2025.
  • Social commerce is expected to reach $660 billion globally and $80 billion in the U.S. by 2025, up from $295 billion in 2021.
  • According to the survey, 76% of respondents said they plan to increase their spending on TikTok in 2023, and 44% plan to increase investment in Amazon.
  • As digital commerce gets more competitive, more brands will shift to a decentralized approach to incorporate e-commerce across their organizations.
  • In the next decade, WARC notes retail media networks will grow like search advertising did in the 2000s and how social media grew in the 2010s.

Direct quote

“Because of its Chinese ownership, TikTok has to solve a problem. Their COO says the servers are located outside China and  that the Chinese management leave the TikTok management a lot of room in decision making. But the anti-China rhetoric is a bipartisan issue. That issue remains extant. At [a recent] meeting in D.C., we had a discussion about whether it was likely that the rhetoric against China would be reduced on both sides of the House of Representatives. I was told vehemently that it would not. The more problems that TikTok has, the better it is for Facebook. TikTok [has] to sort out what they’re going to do about their corporate structure.”

— S4 Capital’s Sir Martin Sorrell on political headwinds TikTok will face

Speed reading

https://digiday.com/?p=482242

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Michael Bürgi

WSJ, Insider, BDG among publishers revisiting pandemic lessons in business ops as potential recession looms

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WSJ, Insider, BDG among publishers revisiting pandemic lessons in business ops as potential recession looms

This article is part of a limited editorial series, called The 2023 Notebook, and is designed to be a guide to marketing and media buying in the new year. Explore the series here.

After learning fast on their feet in 2020, publishers had to make some changes to the way they conducted business. Nearly three years later, several of those changes are still in place — guardrails media execs now hope will help them weather this pending economic storm.

Sales teams are still operating on tight timelines and are building in flexibility as their most important selling point. Remote working means publishers can continue saving on real estate and can hire strategically based on skill versus location. And if the economy takes a bigger hit than publishers can handle, they’re not afraid to make the necessary expense cuts to right the ship.

“Go back in the time machine to March 2020, one thing that we learned really quickly on the job was the importance of scenario planning,” said Jason Wagenheim, CRO and president of BDG. “We had levers that we could pull to keep our business moving forward, whatever the universe threw at us. So now we’re doing the same thing.”

Flexibility sells

In the pandemic’s first year, publishers’ sales teams had to scrap all of their rules around sale cycles and the timelines for campaign executions to be as flexible as necessary with clients who suddenly lost their advertising budgets. Yes, losing that money in Q2 and Q3 of 2020 hurt, but potentially ruining relationships with top clients by being strict about ad deals would have hurt worse. 

The pandemic’s recession was short lived and by the end of that year, many publishers were able to recoup losses as well as sign on advertisers for hefty 2021 deals. But by mid-2022, advertisers were once again asking for the same flexibility as they determined their budgets for this year. 

Media execs are heading into this year preparing to be flexible or risk losing advertisers to competitors that can offer them better terms.

“It’s never been more crucial to be in consistent communication with your clients,” said Josh Stinchcomb, global CRO at The Wall Street Journal. “The ever-evolving economic circumstances can change the needs of your partners and their businesses, and if you’re not closely aligned and can’t quickly adapt to shifting priorities, you can find yourself behind the eight ball.”

Take Insider, for example. The publisher’s customer success team was born out of the pandemic and was created to provide flexibility from point-of-sale to execution in a way that salespeople and the campaign creatives aren’t equipped to do on their own. 

“When you have clients just getting thrown everything at them from their leadership teams [from] changing deadlines, changing budgets and changing priorities, that means we have to shift gears really quickly. [Even] after the deal is done, [we will have to] reposition ads, change creative, change the lines of stories that we’re telling through our studio,” said Maggie Milnamow, CRO of Insider. 

Operating with a remote workforce

While many publishers have made the return to office on a permanent or hybrid basis, there are several still committed to giving employees the option of working from home as much as they’d like. 

Having fewer employees commuting into an office opens up the possibility for downsizing its real estate footprints as well, typically one of the most significant pieces of overhead businesses have to consider, particularly in a recession.

“Insider has a policy in support of working remotely. We did this very quickly when COVID hit and embraced it. We’ve been consistently supporting remote work here [which] has really transformed so many things for the better,” said Barbara Peng, president of Insider.

Because staffers are scattered around the world, they’ve retained ways of communicating that first started at the beginning of the pandemic. Employees who are sitting in the same conference room, for example, will still video call in individually instead of putting one camera on everyone.

“It’s been better from a communication standpoint,” Peng said. 

Hiring based on skill vs. location

Having the option of working remotely on job listings helped to significantly improve the application pool of employees once companies unfroze hiring plans and moved from survival mode into growth mode. And for publishers that do not mandate in-office days, being able to hire employees outside of major city hubs has helped to improve the diversity of its talent.

“The talent pool is greatly expanded to include people from more diverse backgrounds and geography, but it’s all kinds of diversity,” said Peng. “So not just socio-economic or racial, [but it opens up the talent pool in regards to] neurodiversity, introverts and women. Remote work has also been transformational with people with disabilities — people who never would have been comfortable coming into an office job and commuting from their homes every day.”

In the past year, Insider’s racial diversity has improved marginally, changing the ratio of white staffers to BIPOC staffers from 66:33 in 2021 to 62:36 as of September 2022. 

Taking a page from the cost cutting playbook 

Media execs are in general consensus that the first half of 2023 will be “spooky,” and if things get too bad, Wagenheim said 2020 trained his team to know the exact right levers to pull in case of emergency. 

“It’s right out of an MBA textbook,” said Wagenheim. “Boil it down to careful expense management, hiring freezes and slow rolling hires. We’re not in a place where we’re necessarily executing on any of those things, but we’re very, very thoughtful about every dollar we spend.”

https://digiday.com/?p=481271

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Kayleigh Barber

Agencies plan to focus on TikTok, among other channels, in 2023

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Agencies plan to focus on TikTok, among other channels, in 2023

This article is part of a limited editorial series, called The 2023 Notebook, and is designed to be a guide to marketing and media buying in the new year. Explore the series here.

Even as we start 2023 clouded by economic uncertainty, marketers are looking to digital video, retail media, social media and the metaverse as priorities this year.

Forecasts predict streaming and digital video to grow, as will social media — TikTok especially. Overall, social media is expected to recover, if only slightly coming out of a turbulent 2022.

Media buyers continue to seem to be intrigued by emerging channels, such as the metaverse and live shopping on social media and other commerce platforms, according to five experts who spoke with Digiday. While efforts to participate in the metaverse largely remain experimental, some marketers and planners are optimistic that its retail potential and immersive storytelling could resonate with consumers.

 “GroupM’s end of year report predicts growth in advertising for 2023 to come in at 5.9%, with strong gains in connected TV and retail media in particular — the latter being the fastest growing component of digital in the U.S.,” said John Wittesaele, global CEO at Xaxis, the digital and AI unit at GroupM under WPP.

Here is a look at the channels marketers are eyeing this year:

Streaming and digital video expected to continue to grow

Connected TV and digital video across social platforms will continue to accelerate the market next year. GroupM and Magna had an overall positive outlook for 2023, with digital advertising driving the greatest growth. Social is expected to recover next year after some platforms faced regulatory scrutiny (TikTok) and other tech giants made massive staffing cuts at the end of 2022.

Despite those setbacks, Magna anticipates the global digital advertising to grow by 8% to reach $557 billion, accounting for 65% of total ad revenue in 2023. The growth is driven by e-commerce and media consumption shifts into digital video, the fastest-growing ad format expected to reach $65 billion. Magna points to CTV usage and streaming consumption continuing as “a tailwind for long-form streaming growth.”

Ian Liddicoat, CTO and head of data science at AI advertising company Adludio, agreed that CTV will “become increasingly popular amongst marketers as streaming platforms continue to develop content and direct consumer engagement.”

In particular with streaming services, there is still room to scale for advertisers. Mateusz Jędrocha, head of upper funnel solutions at marketing firm RTB House, said the CTV market seems “far from being saturated,” as the launch of ad-supported plans on Netflix and Disney+ seemed to show. He said this hunger for on-demand content will continue to grow.

“Marketers have been looking closely at OTT video, not only on mobile, but also on CTV,” Jędrocha said. “This premium experience provides a more measurable and addressable alternative to linear TV buying, hence more and more brands are investing heavily in it.”

Where social media channels are headed

Among the social platforms, experts believe advertising dollars will continue to shift toward TikTok in 2023. For Vickie Segar, founder of influencer agency Village Marketing, clients are still spending the majority on Instagram and Facebook. However, she noted they are beginning to shift from experimenting on TikTok to actually diverting dollars toward it from other platforms.

“Our biggest shift, if you were to look at the data across all of our clients, is taking more money from Instagram and pushing it over to TikTok,” Segar told Digiday. “It’s just the very clear number one answer.”

Spending across other platforms such as YouTube and Pinterest remains steady, but the investment in TikTok is increasing faster particularly when it comes to spending on creator content. “2023 is [where we] commit to a 12-month strategy that actually really extends what we’re doing — but don’t give up on Instagram. Reels is becoming much more of a part of the Instagram game,” Segar added.

Magna’s 2023 forecast supports a notable trajectory for TikTok. While social media ad revenue faced a storm of headwinds in 2022 compared to previous years, TikTok was the only platform to post advertising growth while its competitors saw flat or declining ad sales.

The retail potential may also help TikTok’s rise. The platform introduced features such as shoppable ads, “shop this trend” and other creator and commerce solutions in recent years. We may begin to see that brands previously relying on Facebook and Instagram advertising will see “huge success with TikTok ads,” said Ryan Turner, founder of marketing agency EcommerceIntelligence.com.

“We feel that in 2023 we’ll see a sizable shift in social media advertising budgets moving over to TikTok from other channels and networks, especially for e-commerce brands,” Turner said. “The lower prices and built-in viral nature of the content can mean CPMs and CPAs for purchases are much lower… The ad landscape on TikTok is still fairly young and it offers many of the benefits advertisers enjoyed for the first few years of Facebook and Instagram.”

Overall, Oz Etzioni, CEO of ad personalization platform Clinch, added that social media will continue its evolution toward programmatic advertising as they expand their ad-tech offerings. “The process of planning and buying social media will start to more closely resemble programmatic,” said Etzioni. “Third-party solutions will create the fundamental building blocks and define standard taxonomies across social media platforms, unifying workflows and making the overall process easier for everyone involved.”

Will the metaverse or live shopping take off?

It’s too early to tell whether the metaverse or immersive content or commerce trends like live shopping will take off. While live shopping, in particular, became popular in China in recent years, there are mixed feelings for its potential in the U.S. In 2022, Segar said brands wanted to experiment with live shopping and believed it was “going to be the thing” — yet it has not evolved into a part of the social strategy as much as they expected.

“We watched that Asia was ahead of us and that we were going to then follow suit,” Segar said. “And by the holiday of this year, we expected gift guides to be done live… but it is not a table stake part of anyone’s social strategy at all.”

Part of the reason is creators don’t like the QVC approach to selling, she added, so adoption has been slow. She had expected TikTok Live and YouTube Live would evolve into live shopping, but it has not moved in that direction.

However, Richard Jones, chief revenue officer at performance marketing agency Wunderkind, believes there is still potential for live commerce features. Jones said this can become “the quickest way brands can monetize on consumers who are shopping on-the-go and on social media, and showing more interest in the metaverse.”

Speaking of the metaverse, in 2022 we saw many holding company giants and media firms testing out content in the metaverse — from building a campus on virtual reality platforms to partnering with brands on immersive experience for consumers. Some agencies look at it as a way to help guide their clients into the metaverse, but there is still debate on what that will look like in the future.

As Val Vacante, vp of solutions and innovation at Dentsu, previously said, the firm’s goal is to create the right experience for each client. “I’m just a firm believer that you need to be experimenting,” Vacante told Digiday. “We cannot advise clients if we are not playing, exploring, testing, winning, failing, right?”

The metaverse may also be a way to expand current out-of-home advertising applications, said Paul Dimmock, co-founder and director of strategy at media agency Eidgensi. This could be digital audio or other digital out-of-home campaigns that combine with immersive storytelling.

“Within nascent metaverse environments, we’ve already seen how DOOH screens can engage users, while back in the real world, DOOH screens could be harnessed to bring NFTs to life thanks to embedded QR codes or visually engaging creative,” Dimmock said. “The endless creative possibilities of these environments means audiences can be engaged by interactive, immersive content that can help to create a cohesive customer journey across all channels.”

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Antoinette Siu

Why you should embrace the extended reality continuum

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Why you should embrace the extended reality continuum

Check out all the on-demand sessions from the Intelligent Security Summit here.

The emerging technologies of mixed reality (MR) and virtual reality (VR) are afroth with specialized terminology. Beyond MR and VR, this technology space includes terms like augmented reality, augmented virtuality, extended reality, spatial computing, wearable computing, ubiquitous computing and metaverse. By the time you read this, there may be more.

Any “digital realities” discussion obliges a commitment to define terms and contexts. The surfeit of terms can be laboriously exhausting to understand and erode the excitement and interest of the curious outside of innovators and early adopters.

MR and VR are destined to merge into a single entity and are already slowly converging. We should reflect this when speaking about the technology space by being concise when referencing the general and intentional and when diving into nuances.

Luckily, we already have a way of taming the jargon and do not need to expand the already unwieldy lexicon. Extended reality (XR) is the consensus term for “all real-and-virtual combined environments and human-machine interactions.”

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The extended reality continuum

The reality-virtuality continuum describes a digital reality space with endpoints of reality and virtual reality. Mixed reality is the spectrum between the endpoints. From a contemporary perspective, there are clear boundaries between reality and MR, and reality and VR. The MR spectrum is naturally and unreconcilably fuzzy and without well-defined boundaries. Reality and VR are discrete states, but MR is a non-linear gradient.  

Extended reality is the spectrum from MR up to and including VR, or from another perspective, it is the reality-virtuality continuum excluding reality.  We can call this subset of the reality-virtuality continuum the extended reality continuum.

Technological advancements and improved experience design will reduce the significance of the differences between MR and VR, causing users (even sophisticated ones) to become unaware of the differences. Classifications, as defined by the XR continuum, will have meaning only for designers and developers.  

The impact on experience design

It is interesting to imagine that the distinction between MR and VR may not always be as straightforward as it is today. We are seeing early instances of immersive digital experiences being fluid and not distinctly MR or VR. This duality raises questions about how being both MR and VR impacts the quality of user experience.

For the sake of exploration, let us assume hardware and software exist to support both high-quality MR and VR experiences. The form factor is immaterial, but to aid the imagination, think of Geordi La Forge’s visor (Star Trek: The Next Generation), any helmeted character in Star Wars (Darth Vader, the Mandalorian, stormtroopers), or an implanted device (contact lens or eye replacements) like in Black Mirror’s “The Entire History of You” (S1E3).

Several questions immediately arise when considering the impact of multidimensional extended reality on experience design. What are the benefits and detriments of an experience having multiple postures in the XR continuum? Can a single experience successfully go back and forth between MR and VR? Can a single experience successfully cover multiple stops in the MR spectrum? How do we design MR experiences that are actual augmented reality? Where in the XR continuum is the best experience for my users and their problem space?

Here are some of my early speculative thoughts. Designers should declare to be either MR or VR and stay true to that posture, but this thinking should be challenged and validated. Switching between MR and VR, if possible, will likely be through well-defined modalities, or shift so slowly that the user is unaware of any change. However, attempting to be both MR and VR within the same experience is probably a design trap.

For now, it is impossible to do anything more than speculate and experiment. However, we can advance educated hypotheses using past wisdom from interactive experience design.

The impact on hardware

Device hardware will take on this dichotomy too. The most recent wave of stand-out devices, like Oculus, HoloLens, Magic Leap and smartphones (iPhone and Android), have a strong disposition toward either MR or VR. Each device optimizes to enable one experience type or another, but not both, and for good reason. Supporting both creates many technical challenges and can dramatically affect production costs, in addition to the previously mentioned experience design challenges.

However, this is changing, and future device iterations will support both MR and VR experiences. Devices like those from Varjo, Lynx and Meta are screen-based, with passthrough camera capabilities. Passthrough means the device uses an exterior camera to capture what the screen obscures, allowing the user to “see through the screen.” These devices can support MR and VR experiences with high resolution.

The Magic Leap 2 (ML2) can dim the outer lens to create a not-quite-opaque view of reality. This feature is more about improving the visual quality of rendered content and less about a meaningful attempt to enable VR experiences. MR devices fall significantly short of supporting a quality VR experience due to a limited field of view and an inability to block out the physical environment completely.

It is easy to imagine (and hope) for a generation of XR devices — any device capable of supporting any experience along the XR continuum — and not devices solely dedicated to MR or VR. Unfortunately, this may take several years and likely require different form factors than we have today. Still, there will continue to be a market for dedicated MR and VR devices. As the technologies become commoditized, low-cost or solution-optimized hardware will continue to singularly support either VR or MR.

Converging points

Embrace XR as the general anchor point for discussing MR and VR technologies, as it best fits the general expressions of MR and VR. The term supports discussions with a broad audience and within the creator community. There is a cognitive benefit in simplification for all. The extended reality continuum is a grounding structure for technical or detailed discourse that designers and developers require. Settling on a simpler lexicon lets us focus on much more interesting things.

Simplifying and coalescing terminology helps us move beyond the “Can we do this?” phase of an emerging technology and into exploring what experiences the technology can enable. Designers and technologists need to prepare for the full spectrum of XR experiences. Now is the time to explore the XR continuum and establish the experience design principles which will define the future and success of the medium.

We are beginning what I find to be the most exciting and exuberant phase of any emerging technology.

Jarrett Webb is technology director at argodesign

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If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.

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Jarrett Webb, argodesign

My 13 favorite AI stories of 2022 | The AI Beat

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My 13 favorite AI stories of 2022 | The AI Beat

Last week was a relatively quiet one in the artificial intelligence (AI) universe. I was grateful — honestly, a brief respite from the incessant stream of news was more than welcome.

As I rev up for all things AI in 2023, I wanted to take a quick look back at my favorite stories, large and small, that I covered in 2022 — starting with my first few weeks at VentureBeat back in April.

In April 2022, emotions were running high around the evolution and use of emotion artificial intelligence (AI), which includes technologies such as voice-based emotion analysis and computer vision-based facial expression detection. 

For example, Uniphore, a conversational AI company enjoying unicorn status after announcing $400 million in new funding and a $2.5 billion valuation, introduced its Q for Sales solution back in March, which “leverages computer vision, tonal analysis, automatic speech recognition and natural language processing to capture and make recommendations on the full emotional spectrum of sales conversations to boost close rates and performance of sales teams.” 

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But computer scientist and famously fired, former Google employee, Timnit Gebru, who founded an independent AI ethics research institute in December 2021, was critical of Uniphore’s claims on Twitter.  “The trend of embedding pseudoscience into ‘AI systems’ is such a big one,” she said.  

This story dug into what this kind of pushback means for the enterprise? How can organizations calculate the risks and rewards of investing in emotion AI?

12. Cripping AI cyberattacks are inevitable: 4 ways companies can prepare

In early May 2022, Eric Horvitz, Microsoft’s chief scientific officer, testified before the U.S. Senate Armed Services Committee Subcommittee on Cybersecurity, he emphasized that organizations are certain to face new challenges as cybersecurity attacks increase in sophistication — including through the use of AI. 

While AI is improving the ability to detect cybersecurity threats, he explained, threat actors are also upping the ante.

“While there is scarce information to date on the active use of AI in cyberattacks, it is widely accepted that AI technologies can be used to scale cyberattacks via various forms of probing and automation…referred to as offensive AI,” he said. 

However, it’s not just the military that needs to stay ahead of threat actors using AI to scale up their attacks and evade detection. As enterprise companies battle a growing number of major security breaches, they need to prepare for increasingly sophisticated AI-driven cybercrimes, experts say. 

11. ‘Sentient’ artificial intelligence: Have we reached peak AI hype?

In June, thousands of artificial intelligence experts and machine learning researchers had their weekends upended when Google engineer Blake Lemoine told the Washington Post that he believed LaMDA, Google’s conversational AI for generating chatbots based on large language models (LLM), was sentient. 

The Washington Post article pointed out that “Most academics and AI practitioners … say the words and images generated by artificial intelligence systems such as LaMDA produce responses based on what humans have already posted on Wikipedia, Reddit, message boards, and every other corner of the internet. And that doesn’t signify that the model understands meaning.” 

That’s when AI and ML Twitter put aside any weekend plans and went at it. AI leaders, researchers and practitioners shared long, thoughtful threads, including AI ethicist Margaret Mitchell (who was famously fired from Google, along with Timnit Gebru, for criticizing large language models) and machine learning pioneer Thomas G. Dietterich. 

10. How John Deere grew data seeds into an AI powerhouse

In June, I spoke to Julian Sanchez, director of emerging technology at John Deere, about John Deere’s status as a leader in AI innovation did not come out of nowhere. In fact, the agricultural machinery company has been planting and growing data seeds for over two decades. Over the past 10-15 years, John Deere has invested heavily on developing a data platform and machine connectivity, as well as GPS-based guidance.

“Those three pieces are important to the AI conversation, because implementing real AI solutions is in large part a data game,” he said. “How do you collect the data? How do you transfer the data? How do you train the data? How do you deploy the data?” 

These days, the company has been enjoying the fruit of its AI labors, with more harvests to come. 

9. Will OpenAI kill creative careers?

In July, it was becoming clear that OpenAI’s DALL-E 2 was no AI flash in the pan.

When the company expanded beta access to  its powerful image-generating AI solution to over one million users via a paid subscription model, it also offered those users full usage rights to commercialize the images they create with DALL-E, including the right to reprint, sell and merchandise.

The announcement sent the tech world buzzing, but a variety of questions, one leading to the next, seem to linger beneath the surface. For one thing, what does the commercial use of DALL-E’s AI-powered imagery mean for creative industries and workers – from graphic designers and video creators to PR firms, advertising agencies and marketing teams? Should we imagine the wholesale disappearance of, say, the illustrator? Since then, the debate around the legal ramifications of art and AI has only gotten louder.

8. MLOps: Making sense of a hot mess

In summer 2022, the MLops market was still hot when it comes to investors. But for enterprise end users, I addressed the fact that it also seemed like a hot mess. 

The MLops ecosystem is highly fragmented, with hundreds of vendors competing in a global market that was estimated to be $612 million in 2021 and is projected to reach over $6 billion by 2028. But according to Chirag Dekate, a VP and analyst at Gartner Research, that crowded landscape is leading to confusion among enterprises about how to get started and what MLops vendors to use. 

“We are seeing end users getting more mature in the kind of operational AI ecosystems they’re building – leveraging Dataops and MLops,” said Dekate. That is, enterprises take their data source requirements, their cloud or infrastructure center of gravity, whether it’s on-premise, in the cloud or hybrid, and then integrate the right set of tools. But it can be hard to pin down the right toolset.

7. How analog hardware may one day reduce costs and carbon emissions

In August, I enjoyed getting a look at a possible AI hardware future — one where analog AI hardware – rather than digital – tap fast, low-energy processing to solve machine learning’s rising costs and carbon footprint.

That’s what Logan Wright and Tatsuhiro Onodera, research scientists at NTT Research and Cornell University, envision: a future where machine learning (ML) will be performed with novel physical hardware, such as those based on photonics or nanomechanics. These unconventional devices, they say, could be applied in both edge and server settings. 

Deep neural networks, which are at the heart of today’s AI efforts, hinge on the heavy use of digital processors like GPUs. But for years, there have been concerns about the monetary and environmental cost of machine learning, which increasingly limits the scalability of deep learning models. 

6. How machine learning helps the New York Times power its paywall

The New York Times reached out to me in late August to talk about one of the company’s biggest challenges: striking a balance between meeting its latest target of 15 million digital subscribers by 2027 while also getting more people to read articles online. 

These days, the multimedia giant is digging into that complex cause-and-effect relationship using a causal machine learning model, called the Dynamic Meter, which is all about making its paywall smarter. According to Chris Wiggins, chief data scientist at the New York Times, for the past three or four years the company has worked to understand their user journey and the workings of the paywall.

Back in 2011, when the Times began focusing on digital subscriptions, “metered” access was designed so that non-subscribers could read the same fixed number of articles every month before hitting a paywall requiring a subscription. That allowed the company to gain subscribers while also allowing readers to explore a range of offerings before committing to a subscription. 

5. 10 years later, deep learning ‘revolution’ rages on

I enjoy covering anniversaries — and exploring what has changed and evolved over time. So when I realized that autumn 2022 was the 10 year anniversary of groundbreaking 2012 research on the ImageNet database, I immediately reached out to key AI pioneers and experts about their thoughts looking back on the deep learning ‘revolution’ as well as what this research means today for the future of AI.

Artificial intelligence (AI) pioneer Geoffrey Hinton, one of the trailblazers of the deep learning “revolution” that began a decade ago, says that the rapid progress in AI will continue to accelerate. Other AI pathbreakers, including Yann LeCun, head of AI and chief scientist at Meta and Stanford University professor Fei-Fei Li, agree with Hinton that the results from the groundbreaking 2012 research on the ImageNet database — which was built on previous work to unlock significant advancements in computer vision specifically and deep learning overall — pushed deep learning into the mainstream and have sparked a massive momentum that will be hard to stop. 

But Gary Marcus, professor emeritus at NYU and the founder and CEO of Robust.AI, wrote this past March about deep learning “hitting a wall” and says that while there has certainly been progress, “we are fairly stuck on common sense knowledge and reasoning about the physical world.” 

And Emily Bender, professor of computational linguistics at the University of Washington and a regular critic of what she calls the “deep learning bubble,” said she doesn’t think that today’s natural language processing (NLP) and computer vision models add up to “substantial steps” toward “what other people mean by AI and AGI.” 

4. DeepMind unveils first AI to discover faster matrix multiplication algorithms

In October, research lab DeepMind made headlines when it unveiled AlphaTensor, the “first artificial intelligence system for discovering novel, efficient and provably correct algorithms.” The Google-owned lab said the research “sheds light” on a 50-year-old open question in mathematics about finding the fastest way to multiply two matrices.

Ever since the Strassen algorithm was published in 1969, computer science has been on a quest to surpass its speed of multiplying two matrices. While matrix multiplication is one of algebra’s simplest operations, taught in high school math, it is also one of the most fundamental computational tasks and, as it turns out, one of the core mathematical operations in today’s neural networks. 

This research delves into how AI could be used to improve computer science itself, said Pushmeet Kohli, head of AI for science at DeepMind, at a press briefing. “If we’re able to use AI to find new algorithms for fundamental computational tasks, this has enormous potential because we might be able to go beyond the algorithms that are currently used, which could lead to improved efficiency,” he said. 

3. Why authorized deepfakes are becoming big for business

All year I was curious about the use of authorized deepfakes in the enterprise — that is, not the well-publicized negative side of synthetic media, in which a person in an existing image or video is replaced with someone else’s likeness.

But there is another side to the deepfake debate, say several vendors that specialize in synthetic media technology. What about authorized deepfakes used for business video production? 

Most use cases for deepfake videos, they claim, are fully authorized. They may be in enterprise business settings — for employee training, education and ecommerce, for example. Or they may be created by users such as celebrities and company leaders who want to take advantage of synthetic media to “outsource” to a virtual twin.

Those working in AI and machine learning may well have thought they would be protected from a wave of big tech layoffs. Even after Meta layoffs in early November 2022, which cut 11,000 employees, CEO Mark Zuckerberg publicly shared a message to Meta employees that signaled, to some, that those working in artificial intelligence (AI) and machine learning (ML) might be spared the brunt of the cuts.

However, a Meta research scientist who was laid off tweeted that he and the entire research organization called “Probability,” which focused on applying machine learning across the infrastructure stack, was cut.

The team had 50 members, not including managers, the research scientist, Thomas Ahle, said, tweeting: “19 people doing Bayesian Modeling, 9 people doing Ranking and Recommendations, 5 people doing ML Efficiency, 17 people doing AI for Chip Design and Compilers. Plus managers and such.”

1. OpenAI debuts ChatGPT and GPT-3.5 series as GPT-4 rumors fly

On November 30, as GPT-4 rumors flew around NeurIPS 2022 in New Orleans (including whispers that details about GPT-4 will be revealed there), OpenAI managed to make plenty of news. 

The company announced a new model in the GPT-3 family of AI-powered large language models, text-davinci-003, part of what it calls the “GPT-3.5 series,” that reportedly improves on its predecessors by handling more complex instructions and producing higher-quality, longer-form content. 

Since then, the hype around ChatGPT has grown exponentially — but so has the debate around the hidden dangers of these tools, which even CEO Sam Altman has weighed in on.

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Sharon Goldman

What’s in store for cybersecurity in 2023

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What’s in store for cybersecurity in 2023

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This past year was an impactful one across the cyber threat landscape. Ransomware continued to dominate the conversation as organizations of all sizes and industries suffered disruptions, often in a visible and public manner. 

The war in Ukraine provided visible examples of a government leveraging both its official and unofficial cyber resources, with Russia using advanced intrusion groups, a larger cybercriminal ecosystem and a varied misinformation apparatus. All of these entities conducted a wide range of malicious cyber activities from destructive attacks, to espionage intrusions, to information operations.

More traditional threats also continued to impact organizations across the globe. Business email compromise remained one of the most financially damaging crimes. Cybercriminals discovered new ways to monetize their efforts while still leveraging tried and true methods. Various government organizations conducted wide-ranging activities to track individuals or steal intellectual property. 

On top of all of this activity, some of the most high-profile intrusions were conducted by low-level actors like Lapsus$.  

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In short, 2022 provided virtually every type of possible malicious cyber event, as well as the highest-ever volume of intrusions.

So, what might we expect for cybersecurity in 2023? Here are five predictions:

2023 cybersecurity: Ransomware will shift its primary focus away from encryption

In 2022, we saw a demonstrable rise in ransomware events involving data theft combined with encryption events. While this wasn’t new to 2022, attackers’ preference for varied extortion options became much clearer. This trend is likely to accelerate in 2023 along with a growing focus on data destruction to include a renewed focus on data backups. These increases are likely to see a corresponding decrease in encryption events.

Why is this likely to happen? Three reasons are at play.  

First, technology and shared best practices are improving ransomware victims’ ability to recover their data without having to pay the attacker for a decryptor. Tied to this, multiple public discussions have revealed that paying for decryptors often results in lost data or follow-on ransom demands, which is why the FBI recommends against paying the ransom..

Secondly, cybercriminals have realized that the “hack and leak” component of a ransomware event provides a second extortion option or subsequent way to monetize their efforts. This becomes more pronounced as regulations and governance requirements become more commonplace. 

Thirdly, it takes more technical work to make an effective encryption/decryption tool compared to stealing data and then choosing a range of methods to corrupt victim data. It’s likely a lower technical lift for ransomware actors to steal data, offer to “sell it back,” and if not, threaten to publicly leak the data or sell to other malicious actors. At the same time, data destruction can place an extreme stress on the victim, which acts in the cybercriminal’s favor.

The most impactful intrusion vector will be SSO abuse

As more organizations move to single-sign-on (SSO) architectures — particularly as an effective way to manage hybrid environments — malicious actors are realizing that this is the best and most effective route to access victims. This past year had multiple high-profile intrusions leveraging malicious SSO with multi-factor authentication (MFA) abuse, which in turn is likely to accelerate this shift.  

Malicious SSO use can be difficult to detect and respond to without effective safeguards in place.  These additional challenges on defenders provide visibility gaps for malicious actors to evade detections. While it is unlikely malicious SSO use, particularly combined with MFA, will be the highest volume threat vector, it provides significant access and the potential to remain undetected across an enterprise. Based on these combined factors, the most impactful intrusions of 2023 will combine these actions.

Low-level actors will produce high-level impacts

The threat landscape continues to become more varied and diverse with each passing year. These changes are providing more capability for entry-level threat actors. The increased capability, in turn, produces much more substantive impacts to their targets.

In the past, malicious threat actors had to conduct virtually all technical and monetization actions on their own. This technical standard, while not preventing all impacts, did effectively place some restraints on different threat actors. But that technical requirement is being largely replaced by an effective “intrusion gig economy” where tools, access, or malicious services can be purchased.  

This is combined with a growing list of highly capable offensive security tools being leveraged for malicious purposes. Finally, 2022 provided significant media coverage for low-level actors producing large impacts to mature organizations. These combined factors are likely to produce more impactful intrusions in 2023 from threat actors with lower technical skill levels than in any previous year.

Malicious actors learning cloud intrusions provide cybersecurity detection opportunities

As organizations continue transitioning more of their operations to the cloud and SaaS applications, malicious actors must follow this migration. Put simply, intrusions will have to occur where victims run their operations and host their architecture. These transitions place significant strain on IT staff and often present stumbling blocks or lack of visibility. That’s the bad news.

The good news is threat actors have to make the same transition and stumble through cloud-native aspects of their work, as well. This presents several robust detection opportunities based on potential errors in their tools and methods, lack of understanding of cloud/SaaS fundamentals or challenges moving across a hybrid environment.

New regulations will accentuate the cyber poverty line

The cyber poverty line is a threshold dividing all organizations into two distinct categories: Those that are able to implement essential cybersecurity measures and those that are unable to meet those same measures. This concept was first coined by Wendy Nather, head of advisory CISOs at Cisco, and is often used when discussing budgets, security architectures and institutional capabilities.

As multiple new government regulations and policies roll out globally, the number of requirements on every organization is growing at a rate requiring significant resources and capabilities. As one example, the new US Strengthening American Cybersecurity Act signed in 2022 creates reporting requirements and coordination with government institutions. As another example, Gartner estimates that by the end of 2024, more than 75% of the global population will be covered by some form of digital privacy regulations.  

While these regulatory efforts will undoubtedly produce positive results, a large number of organizations will struggle to implement, comply with, or even understand these same cybersecurity efforts. This is sure to increase the gap between organizations above and below the cyber poverty line instead of reducing the difference. This same growing distance is likely to also carry over into cyber insurance and related areas.

As these five predictions show, 2023 is certain to be as action-packed a year in cybersecurity as 2022 was. Fasten your seat belts.

Steven Stone is head of Rubrik Zero Labs at Rubrik.

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Steven Stone, Rubrik

2023 could be the year for large language models

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2023 could be the year for large language models

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The launch of OpenAI’s ChatGPT has the world abuzz about the advanced capabilities of artificial intelligence (AI). How will it transform industries? What does it mean for Google Search? And will it automate away entire professions? These are just a small sampling of the questions many have been asking about the possibilities. But while there are several unknowns about the impact of this technology, one thing is all but certain: 2023 will be the year for large language models (LLMs).

Many applications for LLMs, like assistive writing and summarization tools, are already here and beginning to change the nature of work as we know it — and will become much more mainstream very soon. But the form that this mainstreaming takes and how it will be implemented remains an outstanding question. Here is what the next year could bring.

Large language models: From hype to real change

First off, because there’s so much hype, there’s a good chance that LLMs will be hugely disappointing for some in 2023 as companies will try to market half-baked products as panaceas. LLMs are trained (in part) to give convincing answers, but these answers can be untrue and unsubstantiated. Inevitably, some people will try to rely on them, with potentially disastrous consequences, leading to the further spread of misinformation.   

That being said, those who are more thoughtful in their approach to LLMs have reason to be very optimistic. LLMs will still change the nature of work (even if the aforementioned disappointment tempers expectations). Writing assistants, like Jarvis, which uses AI to write fast marketing content, will be the most obvious example of tools that easily expand their capabilities. Other document editors will likely follow suit, moving generative AI for language from the “early adopter” crowd to the “early majority” crowd.

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What’s perhaps even more interesting is the subtle influence that these AI advancements have on non-generative applications of LLMs. Text classification and named entity recognition (NER) will noticeably improve, enabling a much wider array of applications.

Let’s take data extraction from documents, for example. With the typical accuracy rates of today, the applications are limited. You wouldn’t want to rely entirely on AI to extract and calculate the total dollar value your company spends on SaaS. But with higher accuracy rates, you can rely more and more on that number — starting by relying on it as an estimate, and eventually exceeding the level of trust you might have in another person.

What’s to come for LLMs

One of the larger outstanding questions of ChatGPT is whether it will lead to mass job elimination. The answer is no. But foundation models will embolden challengers to established business models and practices. For example, in the world of media, small outfits will be able to produce high-quality content at a fraction of the cost (what Corridor Video did with Stable Diffusion and the “Spider-Man: Into the Spiderverse” movie, for instance).

Content writers will be able to deliver high-quality articles at an unprecedented rate, and customer service teams will be able to respond to customer requests that much faster. Small, tech-enabled legal practices will also be able to challenge established partnerships, making it easier for small businesses to automate what they previously outsourced. 

There’s no doubt that the leap forward with ChatGPT will enable a whole host of exciting possibilities. Many elements of this new technology will start to become pedestrian. We hardly bat an eye when Google autocompletes a search query for us, or when our phone auto-suggests relevant text message replies. I often forget how magical voice-to-text technology used to feel (and how text-to-voice seems to get better every day).

While it’s easy to get lost in the AI craze, it’s important to understand the realities of where this technology fits in the context of the broader tech environment. Next year, LLMs will power magical, generative features that people everywhere will use. And by the end of the year, the features that were most transformative, that changed industries the most, and that people come to rely on, will also feel pedestrian.

Cai GoGwilt is the CTO and cofounder of Ironclad

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3 AI trends in drug discovery that stood out in 2022

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3 AI trends in drug discovery that stood out in 2022

DeepMind AlphaFold 2 database

AlphaFold 2’s prediction of a malaria parasite protein.

Image Credit: DeepMind

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There’s no doubt that 2022 saw a wild ride of AI innovation and use cases for business in many industries. AI has extended beyond marketing, customer satisfaction and employee retention. One area where it has made major inroads is medicine, biotechnology and pharmacology, where it is transforming drug discovery and development.

The cost of discovering and developing a drug averages $1.3 billion and “demands anything from 12 to 15 years to hit the market,” according to a PubMed paper. So it’s not surprising that the drug discovery industry has seen a significant rise in AI-powered technologies. A case in point is a paper in Nature that notes that the integration of AI into the drug discovery and development pipeline has increased almost 40% annually.

According to healthcare investors Tzvi Bessler and Morris Laster, Ph.D., “drug discovery companies are leveraging AI in a variety of ways, such as using machine learning algorithms to identify potential drug candidates, predict their effectiveness and safety, and optimize their design. For example, they use AI to analyze large datasets of biological and chemical information to identify patterns and relationships that may be relevant to drug discovery.”

This, they said, helps the companies “identify promising leads and accelerate the drug discovery process.”

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As the year in AI ends, VentureBeat spoke to several experts on 2022’s most compelling AI trends in drug discovery. Here are three trends that stood out:

1. More efficiency in biology modeling and drug target discovery

James Handler, professor at Rensselaer Polytechnic Institute and chair of the Association for Computing Machinery Technology Policy Council, told VentureBeat about two uses where AI is showing great promise in drug discovery: reducing the number of potential candidates for trials, and providing potential explanations for the secondary use of drugs — that is, why a drug shows efficacy for a condition it wasn’t originally designed to treat.

In both cases, he noted, the key is that “AI can reduce the number of possibilities that need to be explored through traditional means.” This aids in biology modeling and drug target discovery. “However,” he added, “an important aspect of this is the AI systems being able to explain their predictions to humans, a focus of current research. This allows humans to make the final decisions [on] analysis and testing, with AI drastically reducing the cost of getting successful drugs to market.”

Drug discovery and development typically begins with identifying a biological target — a gene, protein, receptor or enzyme, for example. Proteins are the most common drug targets because of their ability to influence a cell’s behavior or function. So traditional drug discovery efforts have involved selecting specific proteins with pockets that can be influenced by promising drug-like molecules (which then become the ligand, or binding drug).

However, this process is computationally challenging. Of the 20,360 human proteins stored in the SWISS-PROT — the world’s most widely-used, expertly curated protein sequence database — only a few have been explored as drug targets.

Organizations are now using AI’s ability to correlate and match large amounts of data, leading to more efficient drug target identification and discovery. In 2022, many AI-powered healthcare enterprises channeled resources toward building advanced modeling tools that not only model biology but also identify and validate new targets. This year, major pharmaceutical enterprises like AstraZeneca and Pfizer partnered with AI vendors that offer target discovery-as-a-service to discover over eight new targets.

2. Improved protein structure prediction

Proteins need to be folded into specific three-dimensional structures. Incorrect or absent folding has been linked to the pathology of many diseases. Predicting protein structure is also relevant in the drug discovery process because it provides a better understanding of how the protein works, thereby informing how it can be affected, controlled and modified.

This is a difficult task, however. One computational biology research report noted that protein structure prediction “remains a prevailing challenge.”

However, 2022 inspired significant progress in predicting how proteins fold. This was spearheaded by DeepMind’s innovative open-source software, AlphaFold, which can predict a protein’s 3D structure from its one-dimensional amino acid sequence. AlphaFold was able to predict the protein structures of “nearly all cataloged proteins known to science.”

Reducing what would typically take years to mere seconds, in July the software used the power of AI’s deep learning to predict and publicly share over 200 million protein structures belonging to animals, plants, bacteria, fungi and other organisms.

In November, DeepMind’s AI model found a worthy rival in Meta’s research team. Meta leveraged AI’s natural language processing (NLP) abilities and applied “a large language model” to predict the structure of over 600 million proteins found in both known and unknown organisms. This is a great advancement for protein structure prediction, formerly a major challenge.

Image from the National Library of Medicine through the National Center for Biotechnology Information highlighting the different drug discovery domains where AI can function. Find the full essay here.

During de novo drug design (DNDD) — which PubMed describes as “the design of novel chemical entities that fit a set of constraints using computational growth algorithms” — molecules are developed from scratch, allowing for shorter trial-and-error phases. As de novo is typically a generative type of design, it relies largely on computational processes and deep learning models.

2022 has witnessed significant progress in the development of de novo approaches that incorporate reinforcement-learning architectures in regular AI neural networks.

The virtual screening of existing databases, another aspect of drug design, was also an object of attention in 2022. Combing through large databases for similarities and spotting specific peculiarities are defining features of AI. Pharmaceutical giants applied this technology to large volumes of databases and invested millions of dollars in partnerships with AI platforms capable of virtually screening trillions of synthesized compounds.

Handler noted that drugs that seem to be effective in animal testing often fail when they reach human trials. The challenge is predicting toxicity from the earlier data, he said. “New techniques are exploring how to use AI models that integrate the many kinds of test data to predict toxicity better and consequently reduce the number of candidates needing expensive testing.”

Handler added that more data is becoming available and shared, and predicts that “this should create many opportunities for innovation in drug discovery” going into 2023. As VentureBeat reporter Ashleigh Hollowell noted in a recent article, “progress, not perfection, is what to expect [from AI applications] in 2023” — including in the complex world of drug discovery.

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Kolawole Samuel Adebayo

Cyber security professionals share their biggest lessons of 2022

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Cyber security professionals share their biggest lessons of 2022

The past 12 months have been a trying time for cyber security professionals globally. Most notably, they’ve had to contend with a rise in cyber attacks linked to the war in Ukraine. 

At the same time, a global recession has resulted in mass layoffs across the technology industry. Consequently, cyber security departments are increasingly understaffed and burned out. 

With a new year just around the corner, many cyber security professionals are reflecting on the challenges they’ve faced over the past year and coming up with lessons on how to improve in 2023.

Jake Moore, global cyber security advisor at ESET, believes events such as the war in Ukraine and mass layoffs offer the biggest learning opportunities for cyber security professionals. 

“For 2022, I think the majority of infosec professionals have noticed that resilience is not just a term used in cyber security, but also a term used to describe the ups and downs across the whole industry as a whole,” he says. “From working together trying to mitigate the impact of a cyber war coming out of Russia, right through to tech layoffs across multiple organisations including the all-important security departments.”

He says cyber security professionals, many of whom work for overstretched departments, have displayed “a remarkable level of resilience” in the face of increased uncertainty and constantly evolving cyber attacks.

With this in mind, his biggest lesson is to “expect the unexpected more than ever”. “Nothing in this industry can ever be predicated, but learning is key to the future of its success,” he says.

Don’t always trust popular cloud apps 

People must remember that popular cloud apps aren’t always trustworthy and can be breached by cyber criminals, according to Netskope EMEA chief information security officer Neil Thacker. 

In 2022, he saw many instances of cyber criminals using apps such as OneDrive, GoogleDrive, GitHub, Box and Dropbox to distribute malware and command-and-control (C2) services. 

“Too many organisations continue to allow direct access to these services, without providing any form of inline security control to identify when these are being used and if it is for malicious purposes,” he says.

“The lesson to be learned here is that traffic both to and from cloud apps [software as a service] and cloud infrastructure [infrastructure as a service] must be secured and inspected to identify this type of attack vector and mitigate the risks.”

Phishing goes beyond email 

Another lesson from Thacker is that organisations shouldn’t just rely on simulation exercises and email security to mitigate phishing attacks. He says these two methods aren’t effective enough on their own. 

This is because cyber criminals are increasingly using genuine cloud app links to direct employees to spoofed login pages, tricking them into entering their user names, passwords and MFA information. Cyber criminals even convince many employees to provide access to data through “imposter apps”.

“The lesson learned here is that phishing is no longer an issue confined to email security,” says Thacker. “Search engines, social media and blog sites, along with legitimate services such as Google Docs and Microsoft OneDrive, are all platforms being used in phishing campaigns. 

“It’s therefore crucial that user education begins at the initial click point and happens ‘just in time’. Phishing simulations and email security can be used to enforce the messaging on how to spot and report phishing attacks, but are not all-encompassing when it comes to training and counteracting new phishing methods in 2022 and beyond.”

Invest in modern network and security architectures

Over the past year, Thacker has also noticed that large numbers of organisations have accelerated network security and transformation projects in response to “high inflation, scarce talent and global supply chain disruptions”.

“The triple squeeze [inflation, talent shortages and supply chain issues] in 2022 has meant organisations have been pushed to consolidate and converge their legacy network and security equipment to find efficiencies,” he says

“As companies prepare for a global recession, and the additional risks that come with economic challenges, it’s important to be able to scale up, or scale down network and security spend.”

Thacker says the lesson to learn here is that organisations can aid network and security transformation initiatives through the use of modern network and security architectures, such as Secure Access Service Edge (SASE).

“This can include reducing risk, improving productivity among employees and driving cost efficiencies during a particularly uncertain economic environment,” he adds.

Get the basics right

Threat actors are constantly devising new, sophisticated ways of launching cyber attacks on organisations and individuals, and perhaps this has led many cyber security professionals to “focus on cool vulnerabilities”, according to Forrester senior analyst Tope Olufon.

But he believes this shouldn’t come at the expense of cyber security basics such as asset management, patch management and audits. His biggest lesson of 2022 is that getting the basics right is the “bedrock of effective cyber risk management”.

He also encourages cyber security professionals to increase their understanding of new technologies, while sentiment, culture and personality need to play an even bigger role in security design. 

Olufon also recommends that security professionals work more with their peers in the IT department and other people throughout the business. “Jamie the network engineer likely has context you do not, and listening will make your life easier,” he says.

Privacy is essential

Privacy has always been a crucial part of cyber security, but Rebecca Harper, head of cyber security analysis at compliance specialist ISMS.online, believes it’s the “only future of information security”.

“With numerous countries adopting stricter data privacy regulations, the move towards a privacy-first approach is quickly becoming a necessity,” she says. “For example, Google is phasing out third-party cookies in 2023, while Apple has developed privacy protection features since App Tracking Transparency in iOS 14.5.”

In 2023, she expects privacy legislation to have an even bigger impact on the information security strategies of businesses and governments across the globe. 

Harper’s lesson is that privacy is “essential for re-building consumer trust”. “As the demand for privacy intensifies, so do the consequences of violating privacy,” she says. “Not only are there fines from new laws, but brand perception – and therefore potential sales – are at risk every time privacy is violated.”

Tackling burnout

Considering that cyber attacks are always increasing in number and complexity, it’s understandable how IT security professionals can feel stressed and burned out.

Rick Hemsley, cyber security leader at EY, says business leaders need to understand the pressure faced by cyber security professionals and the impact this can have on their daily lives. 

“Teams need to be able to not just track and measure threats, which is leading to cases of stress and burnout, but instead have the tools to proactively spot and manage them,” he says.

Hemsley also believes the best security leaders will take steps to better understand and improve the operating models of their departments. 

“They are thinking about how their teams are structured, what are appropriate staffing levels, talent development, and how they deliver in-house, co-source and outsource,” he says. 

“These security leaders are also starting to have more data-driven conversations with the C-suite and stakeholders, using threat intelligence aligning it with business strategy, which is allowing them to instead become a catalyst for trusted change.”

Hemsley argues that for businesses looking to innovate sustainably and quickly, they must put cyber security at the heart of all digital transformation initiatives. He explains that “the opening of this new dialogue between the IT teams and the C-suite will be critical moving forward”.

Improving cyber resilience 

As the cyber attack surface grows, there’s an increased need for organisations to shore up their IT security defences and improve their resilience to cyber attacks.

António Vasconcelos, technology strategist at SentinelOne, says organisations must be able to contain, minimise, mitigate and recover from cyber attacks efficiently. 

“This resilience includes protecting your most valuable assets, like personal identifying information and IP, reducing supply chain disruption, and managing damage to your reputation.”

But Vasconcelos warns businesses that they can’t simply buy cyber resilience. Instead, this is something they must earn. 

“Although it will mean different things to different organisations, a few core principles hold true,” he says. “This includes segregating and segmenting higher-value assets from common ones, adopting a least privilege principle or always verify before trust protocol, and breaking the silos of compartmentalised security.

“Frameworks like ZTNA and XDR are accelerators and enablers for organisations to walk the right path to achieve the cyber resilience they need to tackle threats today and tomorrow.”

The year 2022 has been challenging for the entire cyber security industry, and as the Ukraine war and global economic turmoil show no signs of slowing down any time soon, it’s clear that 2023 will pose similar challenges for cyber security professionals. Hopefully, however, these lessons can help them strengthen their defences going forward.

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Elroy Stoval

How does red teaming test the ultimate limits of cyber security?

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How does red teaming test the ultimate limits of cyber security?

An expert ethical hacker reveals how he goes about carrying out a red team exercise

Rob Shapland

By

Published: 29 Dec 2022

Hacking can be a dirty word. It evokes images of a person sitting in the dark with a black hoodie on, hunched over a keyboard, in front of multiple screens, attacking an innocent business, or individuals, online. It automatically generates thoughts of terrible ransomware attacks and cyber criminal gangs with names such as Evil Corp.

But cyber criminals have a foe – ethical hackers. We hack companies to show them their weaknesses so they can fix them before they are breached.

Companies are aware that cyber attacks are increasing by 50% year on year. With organisational spending on cyber security at an all-time high, firms are spending significant amounts on their security infrastructure. I’m often asked: How can we know that our cyber security is working effectively?

My advice to companies is simple – invest in a red teaming test.

Red teaming is the practice of simulating a multi-layered cyber attack that tests the effectiveness of every aspect of an organisation’s security. Rather than running the risk of financial and reputational damage after being hit by a ransomware attack, hire ethical hackers to simulate an attack to unearth vulnerabilities, so that they can be addressed before it’s too late.

“The only real way you can determine the effectiveness of your security is by getting hacked. Red teaming tests employ both virtual and physical methods to probe for weakness, exactly as a cyber criminal would”
Rob Shapland, Falanx Cyber

Cyber attacks – like when Revolut was breached in September 2022, revealing 50,000 customers’ sensitive data – may have been prevented with a red teaming test that would have pinpointed the threat social engineering posed to the team.

For a company to be put through its paces, it needs to be tested through active and proactive attacks of both its virtual and physical systems, using the same tactics, techniques and procedures as cyber criminal groups are using right now. My team typically carries out a red teaming mission in five steps:

  1. We always begin with open source intelligence gathering (OSINT). As with the first stage of any operation, we begin an attack by investigating a company and its employees, gathering inadvertently revealed information. This comes from a variety of sources with a focus on the corporate and staff’s social media pages. We use this to plan our attacks, both cyber and physical.
  2. We then identify internet-facing systems that may have been insecurely configured or have login pages we can access using stolen credentials, as potential access points to break into an organisation.
  3. This is typically supported by email phishing and telephone vishing attacks – two hacking techniques, together known as social engineering. By phone, we call employees to try to have them divulge sensitive login information. Then we send phishing emails using personal information gathered during OSINT to trick employees into revealing sensitive information, like their username and password, or to open an attachment that would let us into their computer.
  4. Last, but certainly not least, is the physical intrusion of their premises. It may surprise you to hear that cyber attacks can happen in person. This is my specialty. To simulate this, we use various tricks and disguises to access the organisation’s offices to compromise its network, plant keylogger devices, or steal valuable information right from under the business’s nose. At Falanx Cyber’s office, we have a wardrobe full of costumes from an everyday plumber to a postman’s uniform, that we wear as a disguise to test whether a company’s security will let unauthorised people into the building.
  5. All these steps combine to allow us to breach the perimeter and access the organisation’s internal network. When we find a successful route in, we will then attempt to escalate our privileges to gain access to sensitive data that a cyber criminal would target. The process culminates in a strategic report, detailing identified weaknesses, and recommendations for making an organisation’s defences more robust.

Red teaming exercises provide a comprehensive look at just about any tactic, vulnerability, or entry point cyber criminals might use to breach your systems. Without one, companies will never know how secure their systems are.

With almost 90% of hacks due to human error, it’s important to test your employees’ cyber defence abilities. And unlike a simulated penetration test, staff are unaware that a red teaming mission is underway against them – almost like a mystery shopper. It truly is the best way to improve overall security, with the bonus of reinvigorating your staff’s commitment to cyber security by putting them through their paces.

This may be unsettling to hear, but the only real way you can determine the effectiveness of your security is by getting hacked. Red teaming tests employ both virtual and physical methods to probe for weakness, exactly as a cyber criminal would. Knowledge is power. Find out what your weaknesses are so you can put in place the defensive and offensive protections to mitigate them.

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Raleigh Fleishman

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