Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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When it comes to artificial intelligence and generative AI enterprises are still weighing options, trying to scale pilots and balance short-term returns and efficiency with long-term business transformation. These businesses are also wrestling with generative AI hype vs. reality.

In 2023, generative AI was top of mind and vendors raced to build out offerings. Now the question is how quickly enterprises will scale up generative AI.

• Why vendors are talking RPOs, pipelines, pilots instead of generative AI revenue
• Generative AI features starting to launch, next comes potential sticker shock

These generative AI disconnects are appearing already in a bevy of surveys, conversations and research. Earnings calls are likely to add a few more generative AI themes to watch.

Here's a look at why the generative AI disillusionment is showing up in multiple places.

Big money is being spent on AI and returns need to follow. You can almost feel the pressure on CXOs when it comes to AI, generative AI and transformation spending. Boards want returns yesterday. According to Boston Consulting Group, 85% of more than 1,400 C-suite executives said they plan to increase spending on AI and generative AI, a top three priority, in 2024.

And expectations may be running ahead of reality. According to Constellation Research's second half 2023 CxO Business Confidence Survey: "Buy-side CxOs are balancing the pressure to invest in the AI space with the need for certainty about the reliability of these new tools. In turn, enterprise tech vendors recognize and predict strong revenue potential in the generative AI space but currently are in the waiting phase of tangible selling and the client's desire to see tangible return on investment (ROI)."

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BCG found that 90% of CEOs are waiting for generative AI to move past the hype and remain in the pilot phase. A report from Deloitte on the state of AI (right) found that 79% of CXOs expect generative AI to drive organizational transformation in less than three years, but the majority are focusing on tactical returns like cost savings over growth and innovation. 

Data is still a big problem and there may not be enough of it. Yes, there's all of the data strategy and architecture work that needs to be done before generative AI pays off. But there is a larger question: Do enterprises have enough data.

Constellation Research CEO Ray Wang said on DisrupTV Episode 348:

"This year, everybody has budget so that they can actually prove that maybe this is the year we actually get some benefit out of AI. But we trend it out even further and we realized that next year is the year. Companies realize that no one will have enough data to get to a level of precision their stakeholders will trust."

Whether companies go with large language models or smaller models, there's a data issue. Wang said:

"The first 80% of data is hard, but that next 90% is just as hard. And that next 95% of data is even harder. You might get to this point where you're only going to gonna get 99% accuracy. Is that good enough? For contact center? Probably. For procurement? No. For health care? Never."

What we learned from customers in 2023 and predictions for 2024

Orchestration is challenging. It's one thing to find a commoditized large language model. It's another thing to tune it and secure your data. And it's another challenge to deliver that last mile experience. Frank Schneider, Vice President, AI Evangelist at Verint, on DisrupTV Episode 348 noted:

"A lot of this is use case driven. Is AI getting the use case accomplished," said Schneider, who added that there's accuracy, performance and trust and each use cases will have different variables of those three core items.

"It's really about orchestrating experiences, technologies, language models and getting things in the puzzle to fit together," said Schneider. "Folks with scar tissue can help answer how that equilibrium is going to work because they've tried multiple things over the years of business transformation, digital transformation and whatever new technology has come out."

"The elegant brilliance is in the last mile. That's where the winners are going to be."

Efficiency is dominating the AI conversation, but real transformation is about solving big challenges. Mark Minevich, Chief Digital AI Strategist, Global Social Innovation Technology Executive & Chair, UN Advisor, Private Investor and Author Columnist, said one of his biggest issues with AI and the topic is that it has been "swallowed by corporate players."

"Corporate players ferociously focus on optimization and efficiencies," said Minevich. "I think you need to repurpose and reposition the mission of AI to focus on solving the greatest challenges and problems. I think it's time for AI to save the world. I'm not here to replace human beings."

However, 65% of CFOs agree that they will deploy digital technologies to automate certain jobs previously performed by humans, according to Deloitte.

AI's role in transformation projects is a work in progress. Citigroup has had an ongoing transformation underway for years and the latest installment includes a reorganization to become flatter and 20,000 layoffs.

Citigroup CFO Mark Mason didn't talk AI on the bank's fourth quarter earnings conference call but did note a lot of spending on IT and transformation.

“Over the past three years, we have invested significantly in our infrastructure, platforms, applications, processes and data.

Roughly 30% of our transformation investments over the last three years were in technology, with the remainder related to non-tech employees and consultants. In 2023, we've seen a shift from consulting expenses to technology and compensation as we've gotten deeper into the execution of our transformation. And you should expect to see this trend continue.

In total, we invested over $12 billion in technology in 2023. Beyond transformation, our technology investments are also focused on digital innovation, new product development, client experience enhancements and areas that support our infrastructure like cloud and cyber."

Wang said in a research report that transformation projects need to have a longer-term view and consider the likelihood of success as well as qualitative benefits.

There are numerous hurdles blocking AI adoption. In a recent survey, IBM noted multiple barriers to AI adoption.

• 33% said their companies had limited AI skills and expertise.
• 25% said there was too much data complexity.
• 23% had ethical concerns.
• 22% said projects were too difficult to integrate and scale.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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This post first appeared in the Constellation Insight newsletter, which features bespoke content weekly and is brought to you by Hitachi Vantara.

The convergence of conferences and healthcare-related themes provided a good overview of the state of healthcare data, AI and disruption.

With CES 2024 featuring a good dose of healthcare and wellness news and JP Morgan 42nd Annual Healthcare conference, there were plenty of items to ponder. Here are vignettes from healthcare disruption front lines.

Healthcare disruption and reassembly ahead

Neil Batra, Deloitte's Global Future of Health Leader, said during a CES 2024 panel that the current health system has been in place for the last 70 years since World War II. He said the health system is comprised of multiple players trying to maximize returns, but the consumer is on the fringes of the overall ecosystem.

"The consumer is the secondary part of the story. What we've observed from other transformations in other industries, is that transformations occur when you have pressure from the outside coming in and incumbent structures have to respond. And that's exactly where we think we are today," he said.

This fragmented market features virtual health challenging brick-and-mortar, novel approaches that threaten existing systems and consumers more in charge of their data, said Batra. These fragmented players reassemble where there's retail health and consumer health.

Batra said:

"We think reassembly is where the magic happens and where the value is going to be created. Incumbents are going to gobble up some of these new movers and create a fundamental transformation of the power structure to sectors that are intertwined, interrelated and integrated with all the great innovation that's occurred in the fragmentation moment. After reassembly we get to this notion of an age of biology on a personalized level. The journey is from being about the rule of thumb to the health of N plus one. We think it's a 20-year journey and we think we're roughly midway through."

Will consumers really leverage their health data?

Batra's vision of healthcare nirvana is one that revolves around the consumer being the CEO of her healthcare. He said:

"The consumer is going to elevate to the CEO of their own health. Armed with information spinning off wearables and other devices and data being translated through AI applications; laymen may be able to understand really complex dynamics. And that moves the healthcare professional from somebody as central figure to one that is now maybe a copilot or a coach."

He said this reformatting of healthcare professional won't happen overnight, but consumers will take charge of wellness, mental health and health overall. Healthcare won't be about sick calls only. Generative AI will result in technology that makes healthcare more consumer-oriented, said Batra.

Dorothy Kilroy, Chief Commercial Officer at Oura, said data quality and ease of use will drive how quickly consumers take charge of their own healthcare. "A lot of people still don't know how to just interpret the data. And so, we're going to have to make sure that it's really user friendly in a way that they can actually action on it," said Kilroy.

Cristian Liu, Director of Partnerships and Go-to-Market Strategy at Google Health said consumers have wearables and data so the tools for healthcare reinvention are there. "Do we have the tools to make sense of this information? I think it's really exciting time because of generative AI and because of artificial intelligence," said Liu.

Much of this health reinvention will depend on enterprise data infrastructure, trust and regulatory issues, said Tom Swanson, Head of Healthcare Strategy and Marketing at Adobe. He added:

"The healthcare industry as a whole has more data than any other industry. The question is, are you using the data in an appropriate way that is actually a value to your consumers? Can you use that data to provide value and build trust to enable your consumers to be a proactive participant in their own wellness? The data is there. Right. But I think the biggest problem that we have as an industry is not using it in a timely manner or being afraid to use it because of legal and regulatory constraints."

Kilroy said it's likely that consumers will push the healthcare industry to transform and clear regulatory hurdles. "I see consumers pushing and demanding for more here," she said.

Dr. Generative AI

Liu said the most interesting part of healthcare reinvention is the data and results interpretation via AI and large language models. "A year ago, we couldn't necessarily throw in all of this data and say what does it means. Today you can throw it all into a large language model and it can predict the pieces understood in really laypersons language and explain to you what's going on. That's so exciting for consumer applications," said Liu.

Kilroy said consumers will look to generative AI as a healthcare partner in phases. "There is certainly a more health-conscious consumer that is being more proactive about their health. I don't think that's everybody yet," said Kilroy. "I do think that is changing, but we still have a long way to go in more literacy of health to the consumer."

Data and generative AI can bridge the gap between what a person is feeling and knowing what's going on inside of the body. "The best data is your own data compared to your average personally, and then see how those little micro experimentations can actually change your life," said Kilroy.

The ability to combine personal data with generative AI interpretation may ultimately depend on data interoperability, said Liu. Consumers have health data. Healthcare systems have data locked up. Sharing is difficult. Incentives to share data, in the form of lower healthcare costs, may knock down barriers.

Data sharing between patients and physicians would also be a boon to the customer experience, argued Kilroy. "I think giving physicians continuous data gives them a bigger superpower. I am more hopeful that working with them than against them is actually going to be what's valuable here," she said.

Nvidia only tech company at JP Morgan's 42nd Annual Healthcare conference

Nvidia's healthcare reach played out on two fronts. First, the company held a special address during CES 2024 and outlined plans to use its Nvidia BioNeMo platform to meld generative AI models, cloud and drug discovery. BioNeMo is a generative AI platform to provide services to develop, customize and deploy foundational models for drug discovery.

In addition, Nvidia said Amgen will build AI models to train on human datasets on its infrastructure. The system is based on Nvidia DGX SuperPOD. Amgen will install the system at its deCode genetics headquarters in Reykjavik, Iceland.

With the CES 2024 news out of the way, Kimberly Powell, Vice President of Healthcare, spoke at the JPMorgan 42nd Annual Healthcare conference.

Powell said accelerated computing and AI are combining to usher in an era of digital biology. Nvidia systems are being used for cell imaging and high dimensional analysis. She added that spatial genomics was another promising area.

"There's another phenomenon that is happening, not only the digitization of biology but also with generative AI, the ability to represent the two things that describe drugs, biology and chemistry in a computer. We can use generative AI to represent it," she said.

Powell likened the shift in biology to computer-aided design and electronic design automation in the chip industry. It's early, but Powell argued that drug discovery will be a huge market, just like chip design and semiconductors.

However, there's still work to do. Powell said:

"Biology and chemistry generative AI models are still quite small. We're still in the very, very early innings compared to other fields like natural language processing and what you're seeing with GPT-3, 4, 5, but we're growing in size and complexity. And so, we still have a lot of progress to be had building larger and more capable models from digital biology data that already exist today and the continuously -- enhancing these models with the data that’s continuously being generated in the labs. So BioNeMo provides the biopharma ecosystem with large scale model training to effortlessly train and scale AI training to thousands of GPUs and you can train billion parameter models in days rather than the months it was taking."

Medtronic eyes AI for growth

Medtronic has formed an AI center of excellence as the company aims to advance AI-enabled healthcare based on data from its medical devices.

Speaking at the JPMorgan 42nd Annual Healthcare conference, Medtronic CEO Geoffrey Martha outlined the company's plans in AI. Martha said the company's move to create an AI center of excellence is aimed at centralizing key data assets including millions of patient datasets, regulatory experience, analytics knowhow, and medical device expertise.

In a nutshell, many of Medtronic's devices today include algorithms and models. The Medtronic AI-enhanced portfolio includes GI Genius, which uses AI for endoscopy, Touch Surgery Enterprise, AiBLE for neurosurgery, MiniMed 780G System for diabetes management, and LINQ, an insertable cardiac monitor.

"We have the data and analytics expertise, and we're continuing to build on that. And this is across multiple disease areas. And we've been working very closely with the regulators on this. We spend a lot of time with regulators around the world, especially the FDA on how to think about AI and health care," said Martha, who added the company is planning to leverage common platforms to scale.

Martha added that's it's early, but Medtronic is already seeing the promise in training models with its data.

"This isn't about ChatGPT. I mean we have to train the models ourselves with a lot of high-quality data, but the impact is amazing here. And I think as we move forward, you're going to hear more and more about this from us," said Martha.

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Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Matt Abrahams, a Stanford University Graduate School of Business professor and author of Think Faster, Talk Smarter, argues that everyone can become better at spontaneous conversation, master small talk and learn the art of paraphrasing and apologizing.

Speaking on DisrupTV Episode 347, Abrahams laid out some tips from his book to ponder. Here's a look at the takeaways.

Everyone can get better at spontaneous conversation. "We can get better at a relatively fast clip," said Abrahams. "There are things you can do that almost immediately help you feel more comfortable and confident communicating in the moment. For example, learning a simple structure, how to package your information that can help a few techniques to manage anxiety can help a lot right away."

DisrupTV Special Edition Episode - Top 15 Books of 2023

Are there differences in generations when it comes to communications? Abrahams said yes and no. This is Abrahams' first year as a professor where all of the students at the Stanford Business School are Gen Z.

He said:

"I've been teaching a long time. I'm old and I've seen lots of shifts and certainly technology like generative AI is changing the way we communicate, and our students are much in many cases more well versed in them. But the fundamental struggles of communicating effectively, confidently, and concisely persist and transcend generations. And it is important that all of us take the time to hone and develop those skills." 

You can prepare to be spontaneous. Abrahams said his method to communicating has a lot of counter intuitive notions. The biggest one is that you can prepare to be spontaneous. It's like practicing sports. You do drills and prepare to play the game and be spontaneous and react."

"The vast majority of our communication in our personal and professional lives is spontaneous. It's not the plan presentation, the pitch or the meeting with an agenda. It's the giving feedback, it's the fixing our mistakes, it's the apologizing, it's the small talk, the answering questions, that's what most of our communication is," said Abrahams. "I've developed a methodology. It has six steps to help us get through it. And the steps divide into two categories, mindset and messaging and with practice and with pushing yourself to get better. All of us can improve in our spontaneous speaking."

Structure matters. Abrahams said:

"Structure is critical to effective communication when we are in the moment, and we are having to figure out what to say. Many of us take our audiences on the journey of our discovery of what it is we want to say. In other words, we just list out information, our brains are not wired to receive lists or process lists. Structure a logical connection of ideas, beginning middle and an end."

Small talk is a big deal. Abrahams said his book has two parts. The first focuses on the methodology and the other homes in situations that require spontaneous speaking. He said:

"I was surprised to find that small talk is what seems to resonate more than the other parts. I thought it would be Q&A and feedback. Many of us struggle with small talk and I am on a personal mission to help rebrand small talk. Small talk is a big deal. Big things happen in small talk. Think about some of your closest friends that you have. How did you get to know them? And how did you get closer? Chances are it was through small talk. Think about some of the most important deals that you've made or learnings that you've had. It happens through small talk. So, we often write it away as a frivolous, necessary evil when in fact, big things happen. So, the question becomes, how do we do it better?

It's about being interested not interesting. We lead with curiosity, lead with questions and lead with observations. That's how you get things started. Once you get started, most people feel more comfortable."

The art of the paraphrase. Abrahams said that there are plenty of people who talk more than they should. Sometimes it's malice or sometimes they're just discovering what they're saying as they go and get lost. When in that situation, utilize the paraphrase.

"One of the top three communication tools everybody should develop is paraphrasing where you highlight or summarize some key point somebody has said. It is critical to shutting somebody down. If somebody is pontificating and going on and on, simply jump in by highlighting some crucial element, comment on it  and then move on. Paraphrasing is a delightful skill that helps you do that. But it doesn't happen by itself. It is always partnered with good listening. You paraphrase and then there has to be a link, a bridge, to something else."

Listening well. Abrahams said you can learn to listen better by listening for the bottom line instead of the top line. Pay attention to context and how something is said. "What's the person really saying? When we listen intently, we actually hear better. If you want to be a better listener, we have to slow things down. We have to slow the pace. Life comes at us fast and furious, and we have to slow down," said Abrahams. "We have to go to a space we can listen in and  allocate space where we can really focus and then give ourselves a little bit of grace to listen intently to what is said and how it is said. Not only to what is said. By giving ourselves a little pace, space and grace, we can all listen better."

He added that better listening also requires eyes, ears and paying attention to the environment.

The art of apologizing. Abrahams said most people struggle with apologies and do it inappropriately. "We don't really apologize. We say we're sorry for how we make people feel vs. what we actually did. We really have to take the time to apologize," he said.

Abrahams added:

"When it comes to apologizing the structure that I teach is AAA just like roadside service here in the United States. AAA will help you. It's three steps and this is the way you can structure a good solid apology. First, you have to acknowledge the incident. What is it that you did? Second, you have to appreciate the consequences for the person and third, you make amends."

There are times when you have to apologize immediately, but others where you can think it through.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Infosys' third quarter earnings highlight enterprise interest in generative AI, large deals and clients that are navigating an uncertain economic picture.

The services provider delivered $4.66 billion in the third quarter and announced large deal wins at $3.2 billion. In the quarter, 59% of revenue was attributed to North America. Infosys added that demand was strong for its Topaz generative AI platform and Cobalt, its cloud services. For the quarter ended Dec. 31, Infosys reported a net profit of $733 million.

Here are some of the takeaways from Infosys CEO Salil Parekh and CFO Nilanjan Roy on the company's earnings conference call.

Generative AI is top of mind for enterprises. Parekh said:

"Almost every discussion with clients involves some element of generative AI. We're working across a large number of clients on different scales, where there are some which are more pilots some which are programs."

Industry demand is uneven. "We have seen impact in Financial Services, Telco and Hi-Tech segments. We see strength in Manufacturing, Energy, Utilities and Life Sciences segment. We are seeing strong traction for generative AI programs leveraging our Topaz capability. We've integrated our generative AI components into our service line portfolio, creating impact for our clients," said Parekh.

Use cases for generative AI emerge across Infosys clients. "We have developed a range of use cases and benefit scenarios across different industries for our clients. Some of these areas are related to client analytics, process optimization, sales, marketing, knowledge analysis, software development, self-service and personalization," said Parekh.

• Automation of IT processes, security, governance, analytics top AI use cases, says IBM survey
• CFOs eye hybrid work, automation, digital transformation in 2024, says Deloitte

He added that Infosys is working with a large bank on a risk analysis program by developing a large language model for them. A food supplier is personalizing food experiences and making operations efficient.

Inflation and an uncertain economic picture are prolonging decisions. "Inflation, uncertain macro and delay in decision-making continues to impact the financial services sector with increasing cost pressures, clients remain cautious on spending and are reprioritizing their programs to deliver maximum business value," said Roy. Telecom was similar.

"Clients are looking at conserving cash, which is visible in delayed decision-making and project deferrals. Our focus on large and mega deals resulted in healthy pipeline and deal wins. Energy, utilities, resources and services clients remain cautiously optimistic about the demand environment with cap in short-term spend," said Roy.

Why digital, business transformation projects need new approaches to returns

Retail eyes generative AI and predictive analytics. "In the Retail segment, cost takeouts and consolidation remain the primary focus for the clients. While discretionary spends remain under pressure, there are pockets of opportunities, leverage generative AI, in predictive analysis, real-term insights and decision support areas. Deal pipeline is strong, though decision cycles remain long," said Roy.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Google Cloud said it will offer free network data transfer to customers that move to another cloud provider or migrate on-premises.

In a blog post, Google Cloud outlined the changes. Data transfer fees have been under scrutiny by customers as well as regulators. Google Cloud's move also puts pressure on Microsoft Azure and AWS to do the same.

AWS, Microsoft Azure, Google Cloud battle about to get chippy

Amit Zavery, VP, Head of Platform at Google Cloud said eliminating data transfer fees is one important move, but also took aim at software licensing. He said:

Eliminating data transfer fees for switching cloud providers will make it easier for customers to change their cloud provider; however, it does not solve the fundamental issue that prevents many customers from working with their preferred cloud provider in the first place: restrictive and unfair licensing practices.

Certain legacy providers leverage their on-premises software monopolies to create cloud monopolies, using restrictive licensing practices that lock in customers and warp competition.

Google Cloud's free data transfer broaches a key topic in hybrid and multi-cloud approaches. Where your data resides equates to lock-in in many cases. Interoperability would offer more choices. The company has an FAQ outlining the details of free data transfers.

More:

• Cloud customers still optimizing spend and should forever

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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OpenAI launched its GPT Store for custom versions of ChatGPT as well as plans for business and enterprise users. In the first quarter, OpenAI will launch a revenue share program for developers based on engagement with payment details to follow.

The launch, which was telegraphed two months ago, was overshadowed by the Sam Altman saga. The launch of the GPT Store illustrates how OpenAI is focusing on its generative AI business and ecosystem again.

Automation of IT processes, security, governance, analytics top AI use cases, says IBM survey

Most of the GPTs at launch were created by the OpenAI team, but the company said users have created more than 3 million custom versions of ChatGPT.

GPTs I tested include:

• The Negotiator on real estate commissions for buying a residential property. I also asked about financial incentives for new cars.
• Mocktail Mixologist for Virgin Mojito recipes.
• Tech Support Advisor, which explained printer issues well. I could see Tech Support Advisor being used with support videos you'd find on YouTube. Enter Google's Bard at some point.
• Web Browser, which uses Bing to aggregate answers and gather information. The question revolved around success rates of running with a knee replacement. "Lack of Concrete Scientific Evidence: There’s not a ton of scientific research on the impact of high-stress exercises like running on artificial knees. Much of the research is retrospective and relies on post-surgery patients reporting their own experiences," said Web Browser.   

OpenAI's GPT Store will highlight featured GPTs from Canva, Khan Academy and AllTrails.

Where's this GPT Store headed for business? It's not a huge leap to see enterprises create custom GPTs for internal support, financial processes and other areas. What remains to be seen is whether enterprises go directly to OpenAI, look to a competitor, use open source or rely on a cloud hyperscale vendor (AWS, Azure, Google Cloud).

While those use case details are being sorted out, OpenAI is launching new business plans. The company rolled out ChatGPT Team, which will be $25 per user/month billed annually or $30 a month billed monthly.

Team includes everything in Plus, the $20 a month plan for individuals, as well as high message caps, the ability to create and share GPTs in your workspace, an admin console, and no training on your data.

Enterprise includes everything in Team and unlimited high-speed access to GPT-4 and tools like DALL-E browsing, SSO, expanded window for longer inputs, no training on your data and customer data retention windows and admin controls and analytics. Enterprise also includes priority support. Pricing wasn't disclosed.

More:

• OpenAI launches ChatGPT Enterprise

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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Hewlett Packard Enterprise said it will acquire Juniper Networks in a deal valued at $14 billion, or $40 per Juniper share. HPE said the purchase will strengthen its networking business and complement its edge-to-cloud strategy.

According to HPE, Juniper will give the company a higher growth business with more free cash flow and margins. HPE will also continue to invest in AI and cloud. With Juniper in the fold, HPE said networking will represent 31% of pro forma annual revenue and more than 56% of operating income.

For HPE, Juniper also enables it to build out AI-focused networking gear. Networking will be included in HPE's hybrid cloud and AI tools delivered through HPE Greenlake. Juniper can also be leveraged in HPE's high-performance computing efforts.

• HPE bets AI, edge, supercomputing workloads will drive growth
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Juniper was projecting revenue growth of 5% to 6% for fiscal year 2023, which was scheduled to be reported Jan. 30, with earnings per share growing at a double-digit clip. Exiting the third quarter, Juniper had an annual revenue run rate of $5.6 billion.

The deal is expected to close in late 2024 or early 2025. If the deal is terminated, HPE will pay Juniper a $815 million fee. 

Key items to note:

• HPE plans to combine Juniper Networks with its HPE Aruba Networking and design an HPE AI interconnect fabric.
• The company said it will create better user and operator experiences with AI.
• HPE said the combination will be accretive to non-GAAP EPS in the first-year post-closing.
• The combination of the two companies is expected to create run-rate annual cost synergies of $450 million within 36 months post-closing.
• Juniper CEO Rami Rahim will lead the HPE networking business and report to HPE CEO Antonio Neri.

Constellation Research analyst Holger Mueller said:

"HPE did not have the critical mass with Aruba for SD-WAN and now it has it. And HPE lacked cloud revenue with the 'AI' and SD-WAN business from Aruba so the deal makes sense. Antonio is a smart guy and plays with the hand he has. 

Basically, HPE has to outexecute Dell in the shrinking on-premises market. HPE is finding more future revenue beyond on-premises than Dell is ... for now."

In a statement, Neri said:

"This transaction will strengthen HPE’s position at the nexus of accelerating macro-AI trends, expand our total addressable market, and drive further innovation for customers as we help bridge the AI-native and cloud-native worlds, while also generating significant value for shareholders."

HPE said it will fund the purchase with $14 billion in term loans that will be replaced by a combination of new debt, convertible preferred securities and cash. HPE said it plans to reduce leverage 2x in two years post close.

On a webcast, Neri said:

"HP will be a new company where networking will be the core foundation of everything we do. We're going to accelerate what we call an AI driven agenda. And that will allow us to capture this massive inflection point.

Rahim said:

"We were born in the era of the internet, and we built the products to help the internet scale for what it is today. Fast forward to today. The biggest inflection since the dawn of the internet itself is artificial intelligence. That's AI and the thing that I am most excited about with this combination is that we will be able to bring the depth and the breadth of the portfolio is necessary. To capture the full market opportunity that AI presents in front of us."

Other items from the conference call:

• Neri was asked whether HPE and Juniper could collaborate ahead of closing. Neri said: "we have to collaborate with the regulators to make sure we do the utmost to accelerate the closing a transaction. That's a very standard process. And, you know, our goal is to get this transaction close as quickly as possible. Both companies have to stay focused on the respective customers and plans."
• Rahim said he was bullish on the combination of Juniper and Ariba. He also said there's a big data center play. "I'm equally excited about the AI data center opportunity where today you can complement the Juniper networking high performance silicon capabilities with compute, storage, networking, Slingshot and the automation capabilities in a way that I think it will be completely unparalleled," he said.
• The security lineup. Rahim and Neri said there is an opportunity to combine security portfolios on-premises, data center, edge and cloud. "Security is a very big part of the competitive thesis here," said Rahim.
• Neri said HPE with Juniper can offer a full lineup of gear and silicon for cloud and AI workloads with edge and supercomputing. 

• Rahim said that Juniper's Junos OS would garner more investment and is the company's "crown jewel.

• The companies were asked about customer service organizations and combining teams. Neri said HPE has kept Aruba's industry focused services team and said the goal is to maintain Juniper's customer services teams.

Juniper had aligned its business around three primary use cases including automated wide area networking, cloud-ready data center and AI-driven enterprise. The company had also been targeting routing in edge, core and 5G networks.

In addition, Juniper also launched Mist AI, a cloud-first AIOps platform that included end-to-end security. Juniper also has recently outlined its software business as it aimed to move beyond networking gear.

Here's a look at Juniper's vision that will now be incorporated into HPE.

Larry Dignan

Editor in Chief of Constellation Insights Constellation Research

About Larry Dignan: Dignan was most recently Celonis Media’s Editor-in-Chief, where he sat at the intersection of media and marketing. He is the former Editor-in-Chief of ZDNet and has covered the technology industry and transformation trends for more than two decades, publishing articles in CNET, Knowledge@Wharton, Wall Street Week, Interactive Week, The New York Times, and Financial Planning. He is also an Adjunct Professor at Temple University and a member of the Advisory Board for The Fox Business School's Institute of Business and Information Technology.  Constellation Insights does the following: Cover the buy side and sell side of enterprise tech with news, analysis, profiles, interviews, and event coverage of vendors, as well as Constellation Research's community and…...

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The most popular AI use cases include automation of IT processes, security and threat detection, governance and business analytics or intelligence, according to an IBM survey.

IBM Global AI Adoption Index 2023, a survey conducted by Morning Consult on behalf of IBM, found about 42% of enterprises with more than 1,000 employees use AI in their businesses. And 59% of AI early adopters say they will boost spending and accelerate adoption.

The IBM survey of 8,584 IT professionals around the world was conducted in November 2023.

Here's a look at the use cases surfaced in the IBM survey with percentage of respondents.

• Automation of IT processes (33%)
• Security and threat detection (26%)
• AI monitoring or governance (25%)
• Business analytics or intelligence (24%)
• Automating processing, understanding, and flow of documents (24%)
• Automating customer or employee self-service answers and actions (23%)
• Automation of business processes (22%)
• Automation of network processes (22%)
• Digital labor (22%)
• Marketing and sales (22%)
• Fraud detection (22%)
• Search and knowledge discovery (21%)
• Human resources and talent acquisition (19%)
• Financial planning and analysis (18%)
• Supply chain intelligence (18%)

Other findings include:

• 38% of IT professionals at large enterprises say they are deploying generative AI and another 42% are exploring it.
• Companies in the financial services industry are most likely to be using AI. Telecommunications is second in adoption.
• 85% of respondents in China said they are accelerating the AI rollout followed by India at 74%.
• 33% said limited expertise is the biggest barrier to accelerating AI adoption with 25% citing data complexity.
• 57% said data privacy is the biggest concern holding back generative AI adoption.

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