AI Adoption and Usage

AI Adoption

The following are links to articles and posts that talk about the adoption and usage of AI and ChatGPT.  The links are in the most recent date order.

VentureBeat - How Microsoft is turning AI skeptics into AI power users

“In 2024, we’ve pivoted to that goal, which starts with understanding the business problems that AI is best positioned to solve,” Stallbaumer says. “We are working on it now, across every function — like sales, finance, HR, marketing — looking at all of the processes, hundreds of processes, and then [determining] the KPIs within those processes where AI can actually make a difference. That’s how we’re thinking about measurement now.”

Diginomica - Is generative AI project success in 2024 a realistic goal? A mid-year reassessment

The AI dissonance factor kicks in - we're now running into a troubling issue I call AI dissonance, where research on generative AI adoption boomerangs from optimistic to cautious (the cautions trace back to concerns on security, data privacy, and trust). Therefore, you can cherry pick an AI study to bolster any AI narrative you want, from 'immature technology' to 'enterprise game changer,' so that doesn't help us much.

Forbes - From Pilot To Production in Generative AI: 3 Lessons Learned

In fact, many companies are well down their data platform journey with key decisions behind them on infrastructure and modern data stacks, but data cleansing continues to be “a journey - not a destination”. In reality, this is actually a two-part journey - first cleaning up current data sets, and then designing the new data build – to be first-time right.

Information Week - How to Avoid a GenAI Proof of Concept Graveyard

While the entire GenAI tech stack might seem complex, don’t get stuck over-analyzing the selection of every technology component. Most cloud providers offer similar LLM options, and the technologies are constantly evolving. Pick the most reasonable, popular LLM without too much emphasis on scientific evaluation. Bigger and better models are being released every week. Ensure the architecture is flexible enough for leveraging APIs and swapping out key components with new ones.

Forbes - A New Study Shows That AI Adds To The Workload And Stress Of Employees

“In some cases, AI tools are expected to solve complex problems instantly, leading to unrealistic expectations from management. When AI fails to deliver immediate results, the burden falls back on employees, who must compensate for the gap, increasing their stress levels. While AI has the potential to revolutionize various aspects of our business, it is crucial to recognize and address the challenges it brings,” Alston pointed out.

Forbes - Business Leaders Still Aren’t Prepared For The AI Revolution

Even tech giants like Google or Amazon, I would argue, have found themselves caught off-guard. Sure, both have developed chatbots and integrated them into their services in a number of ways. But have they captured the potential of AI to radically shift the paradigm when it comes to online search or shopping?

VentureBeat - Betting on AI? You must first consider product-market fit

The AI boom isn’t going to plan. Organizations are struggling to turn AI investments into reliable revenue streams. Enterprises are finding generative AI harder to deploy than they’d hoped. AI startups are overvalued, and consumers are losing interest. Even McKinsey, after forecasting $25.6 trillion in economic benefits from AI, now admits that companies need “organizational surgery” to unlock the technology’s full value.

InfoWorld - Messy data is holding enterprises back from AI

AI systems need gigabytes and gigabytes of clear and accurate data to be effective. They find patterns within data and respond to your requests of what those patterns likely mean and how to leverage the insights for strategic business purposes. Suppose the data lacks hygiene or accuracy or is dysfunctional? You’ll get incorrect inferences for your AI system or perhaps answers you won’t know are wrong until it’s too late.

VentureBeat - Moving beyond AI paralysis

AI, of course, relies on data, and given that data volume is expanding at a wild speed, questions around quality, lineage and long-term storage are more critical than ever. Complicating the issue is the number of disparate tools and technologies used to access and manage that data, causing bottlenecks that hamper AI tools.

Android Headlines - Companies are losing faith in AI, and AI is losing money

The fact of the matter is that the companies propping up this technology (the ones injecting billions of dollars into AI companies) are starting to shy away. They’re not as likely to invest so much money in it. Sure, you can’t go online without seeing an ad for some new AI service. You can’t go on social media without seeing some new AI-generated video that makes you fear for the film industry. But, the people making that possible might be stepping back a bit.

Computerworld - Want ROI from genAI? Rethink what both terms mean

That meant that 2024 has become the year of AI postmortems and recriminations about why projects went sour and who was to blame. What can IT leaders do now to make sure that genAI projects launched later this year and throughout 2025 fare better? Experts are suggesting a radical rethinking of how ROI should be measured in genAI deployments, as well as the kinds of projects where generative AI belongs at all.

yahoo!tech - More than 40% of Japanese companies have no plan to make use of AI: Reuters poll

Asked for objectives when adopting AI in a question allowing multiple answers, 60% of respondents said they were trying to cope with a shortage of workers, while 53% aimed to cut labour costs and 36% cited acceleration in research and development.

VentureBeat - Capgemini digs into the real reasons that gen AI proof of concepts rarely take off

He went on to explain that a big chunk of the reason that data is often referred to as the new oil is because oil’s only useful after refinement. In a world where 50% of business decisions will be made by AI by 2030 — that’s to say, primarily in autonomous supply chain applications — that’s unacceptable from a risk perspective. And it poses a profound risk from a data perspective.

AiThority - New HFS Research and Tech Mahindra Report on Generative AI Adoption Finds Most Significant Risk is Doing Nothing

The report emphasizes that adopting a proactive “doer” mindset can propel enterprises beyond proof-of-concept (POC) stages and pilot projects, enabling full operational deployment of GenAI. Compared to those still in planning stages, enterprises embracing this approach are five times more likely to achieve functional GenAI deployment, showcasing tangible benefits of practical strategies.

AiThority - New EY Research Finds AI Investment Is Surging, With Senior Leaders Seeing More Positive ROI as Hype Continues to Become Reality

“Business leaders are beginning to shape their future by raising strategic AI investments,” said Traci Gusher, EY Americas AI, Data and Automation Leader. “But the survey uncovered significant risks on the path to enterprise-wide AI adoption, including data infrastructure, ethical frameworks and talent acquisition. These are key to fully maximizing AI’s abilities and will allow organizations to differentiate themselves in the marketplace.”

VentureBeat - Top ten ways Intuit is revolutionizing personalization with generative AI

The company launched Intuit Assist in September 2023. It is its first gen AI-powered financial assistant for small businesses and consumers. The tool is integrated with and capitalizes on Intuit’s proprietary Generative AI Operating System (GenOS). It’s designed to deliver personalized financial insights and recommendations across products, including TurboTax, QuickBooks, Credit Karma and Mailchimp.

Computerworld - Renegade business units trying out genAI will destroy the enterprise before they help

One of the more tired cliches in IT circles refers to “Cowboy IT” or “Wild West IT,” but it’s the most appropriate way to describe enterprise generative AI (genAI) efforts these days. As much as IT is struggling to keep on top of internal genAI efforts, the biggest danger today involves various business units globally creating or purchasing their very own experimental AI efforts.

ZDNet - Time for businesses to move past generative AI hype and find real value

The report found that 27% of organizations run generative AI pilots, with 11% tapping the technology in their software operations. About 75% of large enterprises, with an annual revenue of at least $20 billion, have adopted the technology, compared to 23% of organizations with an annual revenue of between $1 billion and $5 billion.

CIO Dive - CIOs resist vendor-led AI hype, seeking out transparency

While early trends indicate enterprise interest in AI is at an all-time high, CIOs can keep the upper hand in vendor conversations by developing a clear understanding of their organization’s risk appetite, auditing provider claims and leveling unnecessary hype.

VentureBeat - Enterprises embrace generative AI, but challenges remain

It is not clear how pouring money into generative AI is affecting departments that could have otherwise benefitted from the budget, and the return on investment (ROI) for these expenditures remains unclear. But there’s optimism that the added value will eventually justify the costs as there seems to be no slowing in the advances of large language models (LLMs) and other generative models.

AiThority - Survey Reveals Only 20 Percent of Senior IT Leaders Are Using Generative AI in Production

Nearly half of respondents (44%) indicated that their current data tools do not fit their analytics and AI needs, and 43% reported that their current data analytics stack does not meet modern infrastructure standards. Another 88% do not have specific tools or processes for managing LLMs.

Diginomica - AI FOMO - a reality check on AI adoption from Freshworks global study

So here’s a thing - four in ten employees believe they use AI at work, but they aren’t actually sure about that or to what extent! Not that this is preventing a lot of them from claiming to be AI experts. In fact, three quarters of IT people think that, as well as nearly two-thirds (65%) of marketing professionals and just over half (52%) of finance and accounting.

SiliconANGLE - AI’s uncertain path: Companies weigh strategy and implementation in 2024

“Every CIO tells me, their bosses are screaming, ‘We need an AI strategy,’ so they’re investing in the technology,” Kerravala said. “But are we going to wind up in a situation where, without a lack of a roadmap of what to do with AI, you bring the technology, and you spend the money, and then it looks like a bit of a failure, because you didn’t know how to implement it properly?”

Forbes - The Promise And Perils Of Building AI Into Your Business Applications

No matter where you may sit on the AI adoption spectrum, it’s clear that the businesses that are embracing AI are winning a competitive edge. But it’s not as easy as plugging an AI model into your existing infrastructure stack and calling it a win. You’re adding a whole new AI stack, including the model, supply chain, plug-ins and agents—and then giving it access to sensitive internal data for both training and inference. This brings a whole new set of complexities to the security game.

yahoo!finance - Ken Griffin is hitting pause on the AI hype, saying he’s unconvinced the tech will start replacing jobs in the next 3 years

“I’ll ask the question, ‘So tell me how you use AI at your firm today,’ and you get these big smiles, and you get these really enthusiastic answers,” he said, “that have almost nothing to do with AI.”

Network World - AI success: Real or hallucination?

The AI deployments that appeal to enterprise IT teams are those with real, measurable gains – such as AI-driven customer support chatbots, using AI to automate network operations, and self-hosted AI models for business analytics.

Diginomica - While some white collar workers may be worried, logistics and transport sectors are optimistic on AI

And it’s easy to see why. According to the report, every single organization using AI reported benefits in terms of improved safety (45%) and employee productivity (42%). Even at this relatively early stage in the life cycle of AI, it’s a pretty impressive thumbs up for the technology.

Diginomica - Accenture clocks up $2 billion in generative AI sales so far this year - with more to come, according to CEO Julie Sweet

Two important caveats here - that’s impressive growth, but gen AI revenues are still a drop in the ocean when placed against Accenture’s quarterly total of $16.47 billion. The other point to note in terms of shaping future growth expectations is that those numbers are coming from “smaller projects as our clients primarily are in experimentation mode”.

Datanami - CalypsoAI Data Powers Everest Group Report That Reveals Generative AI Adoption Trends

Across business functions, IT (51%) and security (15%) exhibit high GenAI adoption rates, followed by legal (14%) and HR (11%).

The top use cases within IT are automated code generation and debugging (35%), enhanced cybersecurity (30%), virtual assistance and support (20%) and software testing and quality assurance (15%).

ZDNet - Enterprises are preparing to build their own LLMs - why that's a smart move

Constructing these foundational models "is complex and expensive," said Vin, who pointed out that internal enterprise models would build upon the capabilities of these models. "These models will leverage the basic skills of foundational models -- such as language understanding and generation, reasoning, and general knowledge. But they need to extend and specialize them to the industry, enterprise and activity context."

InfoWorld - We need a Red Hat for AI

Everyone is doing AI, but no one knows why. That’s an overstatement, of course, but it feels like the market has hit peak hype without peak productivity. As Monte Carlo CEO Barr Moses highlights from a recent Wakefield survey, 91% of data leaders are building AI applications, but two-thirds of that same group said they don’t trust their data to large language models (LLMs). In other words, they’re building AI on sand.

Forbes - Hype To Harmony: Integrating Generative AI Into Complete AI Approach

Some cracks are certainly starting to show. In the months following ChatGPT’s launch, a slew of new GenAI offerings emerged with many eliciting ante-raising amazement that was certainly earned. But together, they also exposed some technical limitations and adoption challenges, leading more companies to adopt a wait-and-see approach, according to BCG.

AiThority - Taking Generative AI from Proof of Concept to Production

Data readiness and the maturity of the technology used are critical factors in the successful transition from POC to production. POCs are frequently developed using datasets that are not representative of real-world conditions, leading to unrealistic expectations about performance in a production environment. Additionally, the technology used in the POC phase may not be mature enough to support scalable deployment.

eWeek - 10 Most Impactful AI Trends in 2024

As we power through 2024, staying ahead of today’s key AI trends is essential for IT professionals and businesses aiming to leverage cutting-edge technologies to drive growth and innovation. Here’s a quick glance at the top AI trends of the year and their potential impacts:

VentureBeat - McKinsey: Gen AI adoption rockets, generates value for enterprises

The biggest increase in adoption is in professional services, and gen AI is (today at least) most often being used in marketing and sales (for content, personalization and sales leads); product and service development (for design development, scientific literature and research review); and IT (for help desk chatbots, data management, real-time assistance and script suggestions). Also, organizations are seeing the greatest cost reduction in human resources.

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Reuters Institute - What does the public in six countries think of generative AI in news?

ChatGPT is by far the most widely recognised generative AI product – around 50% of the online population in the six countries surveyed have heard of it. It is also by far the most widely used generative AI tool in the six countries surveyed. That being said, frequent use of ChatGPT is rare, with just 1% using it on a daily basis in Japan, rising to 2% in France and the UK, and 7% in the USA. Many of those who say they have used generative AI have used it just once or twice, and it is yet to become part of people’s routine internet use.

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TechBullion - Impact Of AI Chat Technology Across Key Industries

AI chat technology is transforming various industries by enhancing customer service, streamlining operations, and improving overall efficiency. From retail and healthcare to financial services, travel and hospitality, e-commerce, and education, AI chatbots and virtual assistants are driving innovation and delivering significant benefits. As these technologies continue to evolve, their impact will likely grow, further revolutionizing the way businesses operate and interact with customers. By embracing AI chat technology, industries can enhance their service delivery, optimize processes, and stay competitive in an increasingly digital world.

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Fast Company – Instagram is training AI on your data. It’s nearly impossible to opt out 

“To help bring these experiences to you, we’ll now rely on the legal basis called legitimate interests for using your information to develop and improve Al at Meta. This means you have the right to object to how your information is used for these purposes. If your objection is honored, it will be applied going forward.”

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Computerworld - Public opinion on AI divided

Age and gender made a big difference: Males aged 18-34 were by far the biggest users at 33%, while only 16% of females in that age group regularly use LLM chatbots at work. Almost half (48%) of workers using LLMs said they had figured out how to use the tools on their own, although this, too, varied by age. Workers under 55 preferred to explore the technology on their own, while those aged 55 or over expressed a desire for formal AI training.

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Diginomica - Clarity may be emerging in AI capabilities pricing. Here's how

Software vendors have poured on the communications blitz to inform customers and buyers that they have started incorporating artificial intelligence into their products. But, they have simultaneously, conspicuously and quietly avoided discussions about what these new capabilities will cost. Hang onto your checkbooks folks as software vendors might be gearing up to wallet-frack your company’s bank account again.

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Information Week - Addressing Trending Questions About Generative AI

The most forward-thinking organizations are creating an ongoing GenAI educational curriculum to build awareness, increase knowledge and foster creation among their staff. This approach feeds a dynamic, iterative process of collecting ideas and use cases in a methodical manner.  

Techradar - Hardly any of us are using AI tools like ChatGPT, study says – here’s why

Even among the people who have used generative AI tools like ChatGPT, Google Gemini or Microsoft Copilot, a large proportion said they'd only used them "once or twice". Only a tiny minority (7% in the US, 2% in the UK) said they use the most well-known AI tool, ChatGPT, on a daily basis.

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Computerworld - Job seekers and hiring managers depend on AI — at what cost to truth and fairness?

The darker side to using AI in hiring is that it can bypass potential candidates based on predetermined criteria that don’t necessarily take all of a candidate’s skills into account or they can contain hidden biases based on how they were trained by their creators. And for job seekers, the technology can generate great-looking resumes, but often they’re not completely truthful when it comes to skill sets.

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VentureBeat - OpenAI is devouring the media industry

The most obvious answer is that in so doing, it gains access to licensed training data that it can use to build powerful new AI models that can write as well as your average Wall Street Journal reporter.

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 ZDNet - I tested Opera's new Gemini-powered AI capabilities and came away impressed

This new integration isn't just about being able to respond more quickly and accurately to queries. Users will also find Opera's Aria AI now includes new features, such as the ability to read responses out loud. It's also capable of rendering images based on queries, thanks to the Imagen 2 model on Vertex AI.

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ComputerWeekly - Why reliable data is essential for trustworthy AI

“Governance is even more critical when delivering AI-infused data products,” Gartner’s Alys Woodward told the firm’s Data and Analytics Summit. “With AI, unintended consequences can emerge rapidly. We’ve already seen some examples of successful implementations of GenAI. These organisations deploy the technology with appropriate guardrails and targeted use cases, but we never know when our AI-infused data products will lead us into trouble.”

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Forbes - Three Change Management Priorities For Seamless GenAI Deployment

It’s also important for employees and customers to be assured that their data privacy will continue to be top of mind as the technology becomes further scaled to be used within day-to-day workstreams. Be sure to communicate that protocols and guidelines will evolve in the spirit of fostering an ethical and socially responsible AI culture. All of this translates to more support and buy-in across the enterprise.

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