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.&nbsp; <br>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… Read more

Matt Lewis is on a mission to make mental health more actionable with a big assist from generative artificial intelligence.

AI150 member Lewis is now CEO of LLMental, which was founded to leverage AI to augment mental wellness. LLMental has two businesses, a B2C enterprise, Rhythmental, leveraging AI to address depression and other mental health challenges, and TransforMental, a B2B enterprise focused on prioritizing workplace wellbeing. LLMental started as a venture designed to enable startups to address health and life sciences challenges. Today, LLMental is focused on augmented mental wellness with the aim of operating multiple businesses addressing various challenges.

Here's a look at the takeaways about LLMental and its approach to mental health.

Focus. Lewis said LLMental is taking a future view of the challenges humans will face over the next few years. "We drew up a list of 17 thorny problems that have perennially gone unsolved and are areas that don't really have any real innovation in them and could potentially benefit from AI native consideration for people that struggle with those challenges," said Lewis.

Lewis said that LLMental chose to focus on quality of life and the intersection of mental health. "In serious mental illness, the conversation has really been about harm avoidance, but that's often where the conversation ends," said Lewis. "But how's your actual quality of life? What's your decision-making capability look like? What are your social relationships? Have you gotten back to the person you were before you were first diagnosed with depression?"

"There's been little assistance for the person who is suffering to go from diagnosed to a design for recovery."

As a result, LLMental is looking to use generative AI and machine learning to help people progress from diagnosis to remission and ultimately recovery to build a better life, he added.

Previously: AI 15O's Matt Lewis on GenAI adoption, psychology and life sciences

The engagement model. Lewis said LLMental's approach revolves arond everyday engagement, but in a way that's not like talking to ChatGPT. The goal is to take a beginner's mind approach to how mental health conditions are treated. LLMental is designed to fill in those moments where you can't get to a therapist or clinician.

Lewis said:

"You'll probably see your psychiatrist, maybe once every three months for about an hour. You'll see a therapist, maybe once every six weeks for an hour. That total time with a clinician adds up to about 24 hours per year, or maybe about one day of every 365 days. On the other 364 days, you're literally left alone, unsupported, with no engagement, no resources and no information. You're just in your head torturing yourself all the time."

LLMental is designed to be a copilot for your mind that can help you architect the life you're meant to live. It's something that helps you scaffold the types of interventions or activities that are helpful, peer reviewed and evidence based to improve your quality of life."

The idea is that patients can get hyper personalized interventions base on various contexts--weather, work, family obligations.

The platform. Lewis said the platform will be gated for people diagnosed for depression and verified with medical records. "That's both a safety and trust consideration so people on the platform know they're only talking to other people like themselves that have their best interests at heart," said Lewis.

LLMental will also offer life plans that are personalized and curated that can contextually adjust based on responsibilities. Think more Spotify than ChatGPT. Lewis said:

"It's not an avatar. It's not a chat bot, per se. It's more of an assistive consideration to help people figure out what they should do and when they should be doing it instead of doom scrolling on social media, which is not helpful. They're doing things that are useful for their mind and for their other relationships that help them progress and build by 10% improvement every day."

LLMental has nearly 2,000 experiences, interventions and activities that have been curated around social interaction, people and roles and purpose. The organizing principles in part revolve around the research of Thomas Insel, who wrote a book Healing about the path from mental illness to mental health. Insel was Director of the National Institute of Mental Health, led the mental health team at Verily and co-founded Mindstrong Health and Vanna Health. "Insel realized what really changes mental illness is this social cure and mix of people, purpose and place," said Lewis.

The tech stack. LLMental is being built on multiple models depending on the use case. "Generative AI does a great job of helping patients come to terms with stages, readiness adoption and meeting them at their level so they can internalize and actually do something," said Lewis. He said LLMental is still being built and later models will have new benefits. "We're evaluating the right path as we go to market and scale up, but it's about summarization and contextualization for a person dealing with a number of challenges," said Lewis. "You need it to be simple, easily understood, annotated and evidence based. If we're doing our job right the user doesn't really see the AI."

Enterprise use cases. While LLMental is focused on serious mental health conditions the company is also homed in on enterprises. The B2B side of the company is TransforMental and that business is focused on companies trying to adopt AI and address transformation; the thesis is that if the leaders of the organization are overly anxious that they won’t have jobs when the transformation is complete, productivity will plummet in the short term and the business will suffer in the long term.. Lewis said:

"Enterprises have the best intentions with trying to adopt AI, but truth be told, it's not going very well in a lot of places. There are some standouts where pilots and POCs do turn into scalable success, but they are exceptions. They're anomalies. There are many more failures than successes. It is our thesis that AI adoption is not succeeding are human factors. This is in the human computer interaction space and the human factor consideration is almost entirely psychological."

Lewis said he has seen organizations where humans were concerned about losing jobs and that fear hampered adoption. When enterprises have a good culture, growth orientation and robust mental health, transformation is adopted faster with better business outcomes. "TransferMental is designed for the mental health wellbeing side of transformation," said Lewis.

More on data, AI and healthcare transformation:

• How ResMed’s data prowess sets it up for AI, sleep health market expansion
• BioNtech, InstaDeep bet on genAI models to advance R&D, drug discovery, cancer treatment
• Welldoc Chief AI Officer Anand Iyer on AI, data and healthcare transformation
• Themes from the healthcare data, AI, disruption front lines
• 8 takeaways from Constellation Research's Healthcare Transformation Summit
• Medtronic aims to leverage medical device data for AI-enabled care
• Google Cloud's healthcare push accelerates with Vertex AI, MedLM, Healthcare Data Engine
• CVS Health’s Transformation Rides on Data, AI and Customer Experiences
• AI Meets Mental Health Assessments: How Futures Recovery Healthcare, Aiberry Co-innovated

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.&nbsp; <br>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… Read more

OpenAI CEO Sam Altman said "we may see the first AI agents 'join the workforce' and materially change the output of companies in 2025 and that the company's ChatGPT Pro plan, which runs $200 a month, is unprofitable.

Yes, Altman was feeling a bit reflective entering 2025 and provided a few thoughts on OpenAI's evolution in a blog post and on X. Here are some of the key points from Altman.

ChatGPT Pro doesn't make money, but the subscription launched a month ago. On X, Altman noted that ChatGPT Pro doesn't make money at $200 a month because more people are using it than expected. While this disclosure made headlines, it's not really a shocker that a new SKU that launched Dec. 5 isn't profitable. OpenAI is in a weird spot where more usage actually raises prices as ChatGPT processes queries. The company will need more individuals to fork over $200 a month (good luck), upsells to business plans and more efficient compute to make the economics work.

2025 in preview: 10 themes in enterprise technology to watch

Agentic AI will unfold in 2025--maybe. "We believe that, in 2025, we may see the first AI agents “join the workforce” and materially change the output of companies. We continue to believe that iteratively putting great tools in the hands of people leads to great, broadly-distributed outcomes," said Altman, who is going with that digital labor theme that other tech executives like Salesforce CEO Marc Benioff are using.

• Agentic AI: Three themes to watch for 2025
• Agentic AI without process optimization, orchestration will flop

AGI is coming, but there's more. Altman said OpenAI is confident it knows how to build AGI, but superintelligence is the goal. He said:

"We love our current products, but we are here for the glorious future. With superintelligence, we can do anything else. Superintelligent tools could massively accelerate scientific discovery and innovation well beyond what we are capable of doing on our own, and in turn massively increase abundance and prosperity.

This sounds like science fiction right now, and somewhat crazy to even talk about it. That’s alright—we’ve been there before and we’re OK with being there again."

OpenAI will need more capital. Not a shocker, but Altman noted the company "had no idea we would need such a crazy amount of capital" when it started. "There are new things we have to go build now that we didn’t understand a few years ago, and there will be new things in the future we can barely imagine now," he said.

Altman feels attacked. Altman said:

"We’ve also seen some colleagues split off and become competitors. Teams tend to turn over as they scale, and OpenAI scales really fast. I think some of this is unavoidable—startups usually see a lot of turnover at each new major level of scale, and at OpenAI numbers go up by orders of magnitude every few months. The last two years have been like a decade at a normal company. When any company grows and evolves so fast, interests naturally diverge. And when any company in an important industry is in the lead, lots of people attack it for all sorts of reasons, especially when they are trying to compete with it."

What was missing from Altman? Talk on compute. How is OpenAI aiming to become more efficient? Should OpenAI use other clouds to train models? Will AI ever be carbon neutral? And the big question: How much money is OpenAI losing per query to ChatGPT?

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.&nbsp; <br>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… Read more

GenAI will fade in 2025 as a core topic as we get off the treadmill that is large language model innovation and start looking at returns. With agentic AI all the rage going into 2025, it’s safe to say it’ll be a key theme for at least the first half, but like every technology development disillusionment isn’t far behind.

With that backdrop, I’ll take a stab at 2025 and what we’ll see ahead. This is an expanded take of what I’m pondering for 2025. The Constellation Research team will outline its 2025 predictions by category and topic on Jan. 7.

Here’s what I’m expecting in 2025:

The year ahead will be more volatile than usual. Enterprises will see a lot of market volatility, potential supply chain issues and must ponder more macroeconomic concerns over things like tariffs. While IT budgets look great going into 2025, rest assured budgets and outlooks will fluctuate dramatically. Likelihood of happening: 95%.

• The art, ROI and FOMO of 2025 AI budget planning
• 2025 in preview: Your reading list

2025 will be the year that AI driven productivity gains move outside of the tech sector. Companies like Exxon and Lowe’s will generate billions in savings and revenue opportunities using AI. This move to real enterprise value will barely be noticed given none of the companies benefiting the most from AI will be considered AI pure plays. Nevertheless, the value is there and the companies that use AI for competitive edge will thrive. Likelihood of happening: 90%.

• 13 artificial intelligence takeaways from Constellation Research’s AI Forum
• Enterprises leading with AI plan next genAI, agentic AI phases
• Enterprises start to harvest AI-driven exponential efficiency efforts
• Generative AI spending will move beyond the IT budget
• Enterprise generative AI use cases, applications about to surge
• Takeaways on successful AI, generative AI projects

Enterprises will wrestle with vendor consolidation as an M&A boom kicks off in technology. A new administration and regulatory regime will mean a variety of mergers. Some of these deals will be great and many will bomb. Wall Street is sure to cheer, but CIOs are going to have to game plan for another Broadcom-VMware scenario that may not be so great for customers. Likelihood of happening; 70% only because I’m not convinced regulators will stand down.

Microsoft and OpenAI will reach an impasse and that frenemy theory of mine will be evident. Microsoft faces risks from being seen as the OpenAI reseller and will have to go out of its way to highlight its model choice. OpenAI has larger ambitions and will simply compete with Microsoft on multiple fronts. There’s too much money at stake for the Microsoft-OpenAI relationship to totally go haywire, but you can expect things to get frosty in 2025. Likelihood of happening: 95%.

Agentic AI will usher in autonomous processes, but enterprises will again find themselves boxed in by platform specific approaches. Ultimately, enterprises will demand that agents work across platforms, data stores and processes. By mid-year, the agentic disillusionment begins because cross-platform communication and negotiation between agents won’t be in place. Lock-in concerns proliferate as much as agents do. Likelihood of happening: 100%.

• Agentic AI: Three themes to watch for 2025
• Agentic AI without process optimization, orchestration will flop

The AI data center buildout will stall due to power constraints, land, regulation and NIMBY. It won’t help that large language models will plateau in their development. Let’s get real: Energy needs are the limiting factor toward the proliferation of AI factories. How do I know that LLMs will plateau? Executives get really touchy when asked about the topic. The reality is that LLMs may not have enough available data to make big gains. This reality doesn’t mean that the enterprise returns won’t be there, but we won’t be wowed as much as we were in 2023 and 2024. Given that this call may be early the likelihood of it happening is 50%.

• GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs
• Multi-cloud computing isn't 'a bunch of separate clouds'

Nvidia growth slows due to tough comparisons, the laws of large numbers and the rise of good enough GPUs from hyperscaler custom silicon. The company remains formidable but there’s a big problem with Wall Street: Is there anyone left to buy Nvidia shares? We all own it somewhere. Nvidia’s financials will continue to look great, but expectations are lofty and all it takes is one real or perceived slip. Likelihood of happening: 70%, but timing is very debatable.

• Nvidia CEO Jensen Huang has a dream...
• AI data center building boom: Four themes to know
• On-premises AI enterprise workloads? Infrastructure, budgets starting to align

Edge computing will become more critical for AI inference workloads and become as critical as hyperscale infrastructure. Why? Data latency and the need to run inference closer to the source. 2025 will be the year where AI meets edge computing. Hell, even the Internet of things is going to matter again. Physical AI will require edge computing and IoT. Likelihood of happening: 35%.

Enterprises will continue to try new revenue models and customers will scream since the op-ex budget is being eaten up by SaaS. Consumption will win out as a model and ride shotgun with seat-based models. More software vendors will run their sales ops through marketplaces, notably AWS marketplace. Vendors are going to pitch consumption and value-based models and customers may or may not go for it. By the end of 2025, the buy side and sell side will agree on a model that’ll work for the AI-driven years ahead. Likelihood of happening: 50%.

Enterprises will need to think through quantum computing strategies as it increasingly will be needed to push competitive advantage and AI forward. Workloads will be moved through the cloud and marketplaces will be critical given that it’s far too early to predict quantum winners. I’ve been saying the upcoming year will be the year of quantum for the last 18 months. Holger Mueller has made that proclamation over the last 3 years. Eventually, blind squirrels find a nut. Likelihood of happening: 50%. Likelihood of happening if quantum stocks continue to go parabolic: 70% just because boardrooms will start asking questions.

ERP comes under fire from multiple corners. Palantir has developed a manufacturing OS and has talked up customer wins. ServiceNow is seen as a platform to ride above ERP. Salesforce is an agentic AI play and could do the same to ERP. SAP is still trying to get customers to migrate to the cloud. Likelihood of this ERP demise: 25%.

Things that didn’t make the cut:

• There will be a massive cyberattack that’ll force enterprises to rethink their recovery best practices. Is that a prediction or just a way of life?
• Return to office moves will be delayed. The only companies that are all-in on return to office are the ones with sunk costs and leases in real estate.
• The IPO market will surge in 2025. Too easy.
• The growth of Google Cloud will overshadow concerns about Google’s core search business being hurt by regulators and OpenAI encroachment.
• TikTok will be shut down and global productivity will surge 30%. The shutdown is a coin flip. And that productivity gain is probably conservative.

Insights archive

• 2024 in Insights: Everything we’ve learned
• Agentic AI: Three themes to watch for 2025
• AWS re:Invent 2024: 7 takeaways after drinking from the firehose
• Nvidia CEO Jensen Huang has a dream...
• GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs
• Enterprise software 2025: Three big shifts to watch
• Constellation Research's Connected Enterprise 2024: All the takeaways
• Agentic AI without process optimization, orchestration will flop
• On-premises AI enterprise workloads? Infrastructure, budgets starting to align
• The art, ROI and FOMO of 2025 AI budget planning
• Intuit's Enterprise Suite could upend midmarket ERP
• 13 artificial intelligence takeaways from Constellation Research’s AI Forum
• Enterprises leading with AI plan next genAI, agentic AI phases
• With Salesforce push, AI Agents, agentic AI overload looms
• Enterprise security customers conundrum: Can you have both resilience, consolidation?
• Big software deals closing on AWS Marketplace, rival efforts

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.&nbsp; <br>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… Read more

Microsoft said it will spend $80 billion on AI data centers to train models and deploy applications in what amounts to a concentrated bet on generative and agentic AI. But there are multiple takeaways to note in Microsoft's missive about its AI plans.

In a blog post, Brad Smith, President of Microsoft, outlined the "golden opportunity for American AI" and argued for its role in the AI ecosystem and a foundation for economic success in the US. The missive comes as an opening act for the Consumer Electronics Show (CES) this week where Nvidia CEO Jensen Huang is going to talk up AI factories and other use cases for its GPUs and AI platform.

Here's a read on Microsoft's post beyond the $80 billion being spent on AI data centers.

Is Microsoft playing data center catch up? Yes, $80 billion is a ton of cash being spent on AI and Microsoft and other tech giants will need to break out checkbooks. But that sum may also mean that Azure needs to be built out rapidly to meet OpenAI demand as well as catch up to Google Cloud and Amazon Web Services. Just an open question, but one worth pondering.

• Nvidia CEO Jensen Huang has a dream...
• AI data center building boom: Four themes to know
• On-premises AI enterprise workloads? Infrastructure, budgets starting to align

Microsoft is clearly wooing a new president in the White House. Tech CEOs are courting President Trump and this Microsoft blog post and its outline for US AI gains is a positioning play. "The country has a unique opportunity to pursue this vision and build on the foundational ideas set for AI policy during President Trump’s first term. Achieving this vision will require a partnership that unites leaders from government, the private sector, and the country’s educational and non-profit institutions," wrote Smith. "At Microsoft, we are excited to take part in this journey."

The software giant hints that Microsoft is more than an OpenAI reseller. Microsoft has noted previously that it's about more than OpenAI models and the company notes Anthropic and Elon Musk’s xAI as rising firms.

Microsoft wants to make sure it doesn't run afoul of antitrust. "Our success, however, depends on a broad and competitive technology ecosystem, much of which is based on open-source development. This includes our longstanding competitors, chip suppliers, applications companies, systems integrators, service providers, and the millions of software developers who use our products to create customized solutions working for our customers," wrote Smith.

Data center buildouts mean blue collar jobs. Microsoft noted that data centers are being built by "construction firms, steel and other manufacturers, and innovative advances in electricity and liquid cooling, all reliant on large numbers of skilled electricians and pipefitters, including members of organized labor unions."

Microsoft dances around job displacement. Microsoft said AI will drive productivity but "disrupt the economy and displace some jobs." Microsoft said it has worked on "skilling initiatives" and is optimistic there will be new economic opportunities.

An export strategy for American AI beyond hardware will be necessary. Microsoft said the race between the US and China for AI dominance will come down to exporting knowhow globally. Smith noted that China has subsidized its telecom industry with Huawei. expanding its reach. "China is starting to offer developing countries subsidized access to scarce chips, and it’s promising to build local AI datacenters. The Chinese wisely recognize that if a country standardizes on China’s AI platform, it likely will continue to rely on that platform in the future," said Smith. "The best response for the United States is not to complain about the competition but to ensure we win the race ahead. This will require that we move quickly and effectively to promote American AI as a superior alternative."

Be wary of regulating too much. "The United States cannot afford to slow its own private sector with heavy-handed regulations. The country instead needs a pragmatic export control policy that balances strong security protection for AI components in trusted datacenters with an ability for U.S. companies to expand rapidly and provide a reliable source of supply to the many countries that are American allies and friends," said Smith. In other words, tariffs and other trade levers may wind up hurting US AI as much as helping.

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.&nbsp; <br>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… Read more

Lowe's has laid the groundwork and is starting to leverage artificial intelligence throughout its operations including store experiences across multiple channels and backend supply chain processes. The plan is to invest in an uncertain market to reap the awards when the home improvement market improves.

The home improvement retailer's focus on its enterprise architecture, data, artificial intelligence and optimization comes amid a rocky real estate market. With fewer homes being sold and inflation concerns, home improvement projects are being put off. Lowe's CEO Marvin Ellison said that Lowe's is seeing customers put off big-ticket purchases such as appliances and a "greater than expected pullback in DIY discretionary spending."

Get this story as a PDF.

"At this point, we're expecting a phased recovery, beginning with homeowners re engaging in smaller refresh and repair projects. Then over time, we expect them to engage in more complex remodels," said Ellison, speaking on an investor meeting in December. Ellison added that Lowe's is looking to win share among Millennials with homes and kids and baby boomers. "These two generations make up the largest share of the home improvement market, and by meeting their needs, we're in position to win across all generations," he said.

Lowe's strategy revolves around the following:

• Grow its revenue by appealing to professional contractors.
• Redesign its loyalty program and step up digital marketing efforts.
• Grow its online sales and omnichannel capabilities to target Gen Z.
• Offer more services with design tools and an online marketplace.
• Continue productivity efforts and leverage generative AI.

The modernization effort

All of those initiatives have a heavy dose of data, AI and enterprise technology. Speaking at Lowe's investor meeting Seemantini Godbole, Chief Digital and Information Officer at Lowe's, said:

"We are using technology to improve our operating efficiency, not only in our stores, but across the organization, and we are looking to leverage the exciting capabilities unlocked by generative AI to enhance our customers and associate experience driving traffic and sales."

Godbole joined Lowe's in 2018 and started an effort to rebuild the retailer's technology strategy, architecture and processes. Lowe's stores were run by systems designed in the 1990s and had merchandising systems from the early 2000s. The company modernized those systems with a focus on omnichannel customer experiences.

Lowe's then set out to build systems to deliver consistent experiences, said Godbole. Key points about the infrastructure updates:

• The company focused on a unified system that provided one view of the customer across multiple channels.
• Associates can access everything needed to serve a customer across multiple channels instead of navigating green screens. "Associates have one intuitive touch screen they can use for everything, even complex sales," said Godbole. "They can look up inventory across the network and even sell products that just arrived at our distribution centers and are yet to be unloaded."
• The omnichannel system includes "all product information, inventory, locations, pricing and promotions and customer orders across every channel."
• The data architecture at Lowe's was built "with AI in mind" and organized so it can be "easily understood and analyzed by AI," said Godbole. "This allows us to easily work across leading AI, large language models, so we can use the right platform depending on the use case," she said.

Lowe's provides a look at how companies leveraging AI have made transformation investments years in advance. There are no overnight AI hits for enterprises.

Godbole said:

"We are now putting in place a framework to help us harness the new power of generative AI for our business to enhance how we sell, how we shop and how we work. This framework helps us standardize the development process so we are using a consistent set of criteria to establish where we use AI regardless of the project. We have built an AI platform that allows us to reuse components and gives us agility to create innovative solutions alongside many of the leading platforms like Nvidia, OpenAI and Palantir."

Lowe's has been one of Palantir's flagship commercial customers.

Also see: How Home Depot blends art and science of customer experience | Scotts Miracle-Gro and UserTesting: 9 customer experience takeaways

50 AI models in production

According to Godbole, Lowe's has "roughly 50 AI models in place" that are used for search, product recommendations, sourcing, demand and planning tools and pricing.

"Now we are using the experience we gained from these first AI models to help us create leading edge solutions that leverage generative AI," said Godbole.

Many of these edge use cases will be used to accelerate online sales with enhanced user experience, customer acquisition and digital commerce. Lowe's app has a style your space feature that is powered by genAI.

Other Lowe's efforts where AI and its data platform are playing a role include:

Localization of assortment. Bill Boltz, executive vice president of merchandising at Lowe's, said the company is expanding private label goods and assortment depending on local market needs. The company is also expanding its efforts in rural areas.

"We're driving space productivity through localization, where we're tailoring our assortments based on demographics, housing sizes, building codes, climate, geography and community preferences, all with the goal of making each Lowe's store feel like your Hometown Store," said Bortz. "We're leveraging AI driven planning tools and insights from our customers and from our field merchants who serve as our boots on the ground to help us understand those local market needs and preferences."

Supply chain optimization. Boltz said the company has been analyzing product components, transportation and raw material costs to verify that supplier charges are warranted. "Leveraging these capabilities, we've worked with our suppliers to claw back some of the costs that we've absorbed due to exceptionally high inflation triggered by the pandemic, and we've worked to then reinvest these savings to drive traffic and sales," said Boltz.

Reducing manual work. Boltz said that Lowe's is focused on reducing manual work, accelerating pricing decisions and optimizing promotions with AI.

Customer data feedback loop. Jen Wilson, chief marketing officer at Lowe's, said the company is using its loyalty program for consumers and contractors to drive a data and consumer insights flywheel. "We built a robust customer data platform, which is transforming our ability to understand our customers and how we market to them," said Wilson. "The more we know about them, the more we can put them at the center of everything that we do, and we can connect with them in more sophisticated ways by offering them a more relevant and personalized experience in anticipating what they need next."

Wilson said the data includes first party data such as purchase behavior and activity on the Lowe's site as well as third party data. "Zero party data," which is information collected through the loyalty program, is also critical because it tells Lowe's whether a customer has a pet, likes to garden and what trades are favored by contractors. Wilson said Lowe's is also adding perks such as digital warranty information attached to appliance purchases.

Efforts to expand professional market share. Lowe's Quonta Vance, executive vice president of pro and home services, said the company has launched a new CRM system to optimize the sales process and personalize offers. Lowe's has also connected directly to suppliers with inventory, pricing and services data. Vance said Lowe's is piloting new fulfillment capabilities for large deliveries.

Services digital payment system. Lowe's is also looking to expand its home services with the ability to make it easy to schedule and pay for installation via smart devices. Customers can now digitally sign a contract and submit payment without a special trip. Typically, customers would have to return to a store to pay for installation for things such as windows, flooring and doors. Associates will also be able to process payments in a customer's home.

"We realized we needed to empower our hard-working front-line associates with better technology and simpler processes so they could be freed from outdated manual tasks and shift their attention to serving our customers and driving sales," said Joe McFarland, executive vice president of Lowe's stores.

Customer experience wins with computer vision

With smart devices, self-checkout terminals and omnichannel improvements mostly in place, Lowe's has set out to leverage AI in ways that can move the needle for customer satisfaction yet operate in the background.

McFarland said the company has been focusing on both associate and customer experiences since it has created "meaningful gains in labor productivity and our operating margin."

According to McFarland, Lowe's proprietary self-checkout registers, improved buy online and pickup in store experiences and optimized front-end selling spaces are just the beginning.

Via a partnership with Nvidia, Lowe's has installed a self-checkout system that uses an AI computer vision tool called Nudge. Nudge detects discrepancies such as a customer that has missed scanning something. Nudge can prod the customer to scan the missing item or alert cashiers to resolve the mismatch.

"Nudge helps us maintain our strong track record managing shrink, and with this assisted self-checkout, we can shift associate time to the sales floor so they can spend more time driving sales and serving customers," said McFarland.

Another interesting customer experience use case is an effort Lowe's calls Dwell. Dwell uses AI vision and algorithms to estimate sales and traffic patterns inside a store. McFarland explained:

"Dwell uses an AI vision algorithm to estimate sales and traffic patterns and see the trends inside of our stores. It uses real time heat maps to see where customers stop in our aisles to look at products and sends associates directly to them to ask if they need help. This new technology will help us staff our stores correctly to maximize sales."

Another use of AI will be embedded into Lowe's companion app for associates. McFarland said the store companion app includes "our very own version of ChatGPT that helps our associates understand what's involved in projects."

The core metrics for these efforts are customer and associate satisfaction scores, operating margin, lower shrink and sales velocity. McFarland said these improvements will also lead to better return on invested capital as Lowe's opens 10 to 15 new stores per year. Lowe's has transformed about a third of its store footprint with new front-end systems and processes.

Supply chain as insights engine

Lowe's has been transforming its supply chain since 2018 to optimize its more than 130 facilities with more than 65 million square feet. The Lowe's supply chain network includes regional, bulk, import and flatbed distribution centers as well as a system of fulfillment facilities.

Margi Vagell, executive vice president of supply chain at Lowe's, said:

"We've transformed our supply chain from a traditional hub and spoke model centered around replenishing stores to one that's more agile, centered around supporting omnichannel fulfillment needs. This multiyear transformation has helped us increase our network capacity, our capabilities to deliver big and bulky items and our flow of product through our distribution centers to our stores. This in turn improves our in stocks and our customer shopping experience and our ability to meet the ever-increasing demand from our DIY and pro customers for fast and flexible delivery options."

Vagell also said Lowe's has deployed a market delivery model for big and bulky products such as appliances. AS a result, bulky products flow from the supply chain to customer homes and job sites instead of stores. Lowe's has been able to double the number of next-day deliveries and improved customer satisfaction by 20 percentage points.

Lowe's said that the company's plan is to further optimize its supply chain and ultimately "make it a proactive sales enabler that drives greater inventory productivity and operational efficiency."

Vagell added that Lowe's has started a three-year project to redesign and modernize its inventory replenishment and demand planning systems. AI will also play a big role in planning for rural locations, rapid store responses and driving insights. Vagell said:

"This new technology ecosystem merges custom and third-party applications that will create a vastly simplified and cohesive experience, resulting in improved forecast accuracy and increased inventory productivity. With these enhancements to our tools and analytics, we will proactively simulate the business and simulate scenarios instead of simply reacting to them."

Lowe's is expecting its merchandising and supply chain efforts to have an impact of $500 million a year in savings and sales and its store operations optimizations to generate another $500 million annually.

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.&nbsp; <br>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… Read more

GenAI and agentic AI were key themes in 2024, but there was plenty of nuance to note as well as common best practices that provide enterprise value.

Here's a look at some of the key takeaways in 2024 from the CXOs in the BT150 based on our numerous interviews and monthly calls.

Sort through the hype vs. reality with genAI and agentic AI. Generative AI and AI agents can drive projects, reshape performance management and impact culture. The problem is cutting through the hype vs. reality of AI adoption. Scaling remains a big issue.

• BT150 CXO zeitgeist: Data lakehouses, large models vs. small, genAI hype vs. reality
• BT150 zeitgeist: AI agent questions, SaaS ate the opex and job woes

Wanted: Real-world value. BT150 members emphasized the need to translate AI innovations into real-world operational value. Process automation was a critical component of genAI efforts and CxOs said there are plenty of returns available with traditional AI approaches.

• BT150's Ashwin Rangan on CIO evolution, technology curves and what it means for genAI deployments
• BT150 Spotlight: Sunitha Ray on the difference between enterprise AI and genAI

Frustration with vendors. BT150 members frequently said they were frustrated with their SaaS vendors for a lack of customer focus, rising costs and questionable ROI. CxOs were also weary of SaaS models that ate up the operating expense budget and wanted tangible business value.

Enterprise buyers ware also struggling with complexity in systems as well as new methodologies.

• BT150 zeitgeist: Dear SaaS vendors: Your customers are pissed
• BT15O CXO zeitgeist: Vendor procurement, cool projects and margin compression
• BT150 CXO zeitgeist: AI trust, AI pilots to projects, VMware angst, projects ahead
• BT150 CXO zeitgeist: Low marks for SAP RISE, process automation, change management, AI risk

Wariness of trending technologies. CxOs said throughout the year that the focus should be on proven results over the latest and greatest in foundational models and data platforms.

Change management matters. CxOs said successful AI projects typically were due to change management as much as the actual technology or vendors.

• BT150 Zeitgeist: GenAI projects and culture, performance management
• BT150 Spotlight: MultiCare Health System's Laurie Wheeler on optimization, change management and healthcare transformation

Use AI projects to drive organizational change. Yes, genAI can drive productivity, but the real win is using those technologies to drive organizational change.

• BT150 spotlight: Omar Jacques Omran on innovation, teamwork

Processes matter. Using AI to scale inefficient business processes will only create headaches. CxOs said that enterprises need to emphasize human-centric approaches and human oversight. Where to put humans in AI-driven processes is the key question.

• BT150 Spotlight: Insight Global's DeWayne Griffin on HR, AI and Humans in the Loop
• BT150 Spotlight: Jewelers Mutual John Kreul on Human-Centric AI, CX, Returns and Futureproofing

See more:

• 2024 in Insights: Everything we’ve learned
• 2025 in preview: Your reading list
• Enterprise software 2025: Three big shifts to watch
• GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs
• The art, ROI and FOMO of 2025 AI budget planning
• Agentic AI: Three themes to watch for 2025

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.&nbsp; <br>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… Read more

With 2025 days away, it’s worth soaking in various outlooks and technology themes that may play out in the year ahead. Here’s a list of reads from Constellation Research and around the web.

• Ray Wang walks through the 7 themes in tech with a new President taking over.
• Blackrock released its macroeconomic and private market themes for 2025. JPMorgan Chase and Goldman Sachs .
• Andreessen Horowitz partners outlined their big ideas for 2025 across multiple tech categories.
• Enterprise software will be volatile in 2025 as customers increasingly question value, complain about upsells and added charges and assess whether agentic AI provides an abstraction layer to their existing applications.
• Andy Thurai outlined the 2025 observability trends you need to know.
• The gap between generative AI's "build it and they will come" folks and the enterprises looking for actual business value may be widening. The next year will be interesting for generative AI trickledown economics.
• Artificial intelligence budgets will surge again in 2025, but good luck tracking expenditures with any precision as generative AI spending is lumped into other categories and driven by multiple departments.
• In 2025, you'll have to get ready for "knowledge," AI governance will move to the forefront, enterprise software models will be revamped, decision automation will depend on humans in the loop and data strategies will be a pain point.
• Artificial intelligence and generative AI will tax leadership, but ultimately raise the bar for decision making. Those were some of the takeaways from Cassie Kozyrkov, Founder Kozyr LLC, who delivered the keynote at Constellation Research's Connected Enterprise.
• Deloitte Insights outlined six macro forces in IT that’ll be evident in 2025.

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.&nbsp; <br>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… Read more

With 2024 ending it’s worth checking in on everything we’ve learned from the CxOs, buyers and sellers of enterprise technology.

Here's everything we learned in 2024:

Some predictions don't quite work out. Yes, I went back into the archive to look at the trends to watch for 2024 published in January. Here's the breakdown:

• Enterprises did refocus on data strategy to make generative AI work and there was a bit of disillusionment with genAI. Not that generative AI was a complete dud, but the reality is that it was a building block on the road to agentic AI. And transformation projects, which included a lot of AI, faced more scrutiny.
• On the flip side of 2024 predictions, that hybrid model for genAI is still on the drawing board, but may appear in 2025. Customers were miffed about enterprise technology price increases, but few did anything about it. I also noted that the economy would be volatile in 2024, but the stock market and leading indicators chugged along for a goldilocks scenario. Tech mergers and IPO remained no shows even though I bet otherwise.My biggest flop was this one: "Enterprises embrace hybrid and remote work and start unloading commercial real estate." You can stop laughing as you read your return to office memos.

See: Constellation Research Presents the 2024 Enterprise Awards | Constellation Research's Connected Enterprise 2024: All the takeaways

Enterprise software is at a crossroads. Enterprise software disruption was a theme we returned to repeatedly in 2024. The seat-based business model isn’t going to fly when AI starts replacing people. Vendors are navigating the rise of marketplaces, models that can keep revenue growth going and balancing margins since genAI isn’t cheap. Most vendors want to be a platform, but we all know there are only a few. Enterprise buyers are pushing back on price increases because software vendors can’t keep gobbling up all the operating expenses.

• Enterprise software 2025: Three big shifts to watch
• Enterprise security customers conundrum: Can you have both resilience, consolidation?
• Big software deals closing on AWS Marketplace, rival efforts
• Disruption is coming for enterprise software
• Enterprise software vendors shift genAI narrative: 'GenAI is just software'

What remains to be seen is whether enterprises buyers have any leverage. Broadcom’s acquisition of VMware caused a lot of complaints, but it’s hard to argue that the deal wasn’t a financial success.

Hyperscale cloud providers are only growing more powerful. Yes, cloud providers give enterprises more agility and save them money. But these hyperscalers hold a lot of power. AWS, Google Cloud and Microsoft Azure had banner years with annual run rates of $110 billion, $45.6 billion, and $156 billion, respectively* . Oracle Cloud Infrastructure did too. What remains to be seen is whether a new breed of cloud providers focused on AI—or even hybrid approaches—can check the market power. AI is a cloud workload—especially since the technology is developing so fast—and looking down the road quantum will be a cloud-first workload too. Whether you standardize on one cloud provider or mix and match infrastructure will be your most important enterprise decision.

*Microsoft doesn’t break out Azure revenue so the run rate is calculated on commercial cloud revenue.

• AWS re:Invent 2024: 7 takeaways after drinking from the firehose
• GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs
• Multi-cloud computing isn't 'a bunch of separate clouds'

AI has impacted industries well beyond technology. AI has become a hot topic on earnings calls beyond the technology sector. GenAI and automation have fueled expanding profit margins at companies such as Lowe’s, Exxon, Rocket and Equifax. Those examples are just a few. The productivity boom from AI has expanded to multiple sectors.

• The art, ROI and FOMO of 2025 AI budget planning
• 13 artificial intelligence takeaways from Constellation Research’s AI Forum
• Enterprises leading with AI plan next genAI, agentic AI phases
• Enterprises start to harvest AI-driven exponential efficiency efforts
• Generative AI spending will move beyond the IT budget
• Enterprise generative AI use cases, applications about to surge
• AWS re:Invent 2024: Four AWS customer vignettes with Merck, Capital One, Sprinkr, Goldman Sachs
• Takeaways on successful AI, generative AI projects

Agentic AI has staying power. Agentic AI pushed generative AI aside for buzzword of the year, but the idea goes beyond vendor marketing. GenAI was a start, but being able to string together models into a flow that automates and executes work is a game changer. There’s a lot of work ahead, but agentic AI is off to a good start.

• Agentic AI: Three themes to watch for 2025
• Agentic AI without process optimization, orchestration will flop

Here’s the digital labor analogy that Salesforce outlined when it launched Agentforce 2.0 this week.

However, the spoils of the AI revolution largely stayed with the infrastructure layer. While AI is promising for multiple industries, the market cap expansion went to infrastructure players. We’re still in the picks and shovels stage of the AI revolution and that means Nvidia has been raking in cash. The big question is when the AI spoils will spread beyond infrastructure.

• Nvidia CEO Jensen Huang has a dream...
• AI data center building boom: Four themes to know
• On-premises AI enterprise workloads? Infrastructure, budgets starting to align
• Blackstone's data center portfolio swells to $70 billion amid big AI buildout bet

Business transformation is alive and well. The Constellation Research community of CxOs continually outlined projects that transform their businesses away from the fanfare. Business transformation is about continual improvement, change management and process. It’s difficult to synthesize all the conversations we’ve had, but here are a few.

• Winners Announced for Most Transformative Business Initiatives of 2024
• Supernova Award Spotlight: How Singapore's M1 Cloud Transformation Led to Personalized Mobile Plans
• BT150 Spotlight: Centurion Health's Johnny Wu on delivering healthcare in prisons
• BT150 Spotlight: Insight Global's DeWayne Griffin on HR, AI and Humans in the Loop
• BT150 Spotlight: MultiCare Health System's Laurie Wheeler on optimization, change management and healthcare transformation
• BT150 Spotlight: Jewelers Mutual John Kreul on Human-Centric AI, CX, Returns and Futureproofing
• BT150 member Dr. Jonathan Reichental: How autonomous vehicles could change how cities are designed
• Peraton's Cari Bohley: Why internal talent recruiting and retention is critical
• SuperNova Award interview with Joe Prota: How IBM used Adobe Firefly to speed up ideation and iteration
• BT150's Ashwin Rangan on CIO evolution, technology curves and what it means for genAI deployments
• BT150 Spotlight: Sunitha Ray on the difference between enterprise AI and genAI

2024 in Constellation Insights

• Agentic AI: Three themes to watch for 2025
• AWS re:Invent 2024: 7 takeaways after drinking from the firehose
• Nvidia CEO Jensen Huang has a dream...
• GenAI's 2025 disconnect: The buildout, business value, user adoption and CxOs
• Enterprise software 2025: Three big shifts to watch
• Constellation Research's Connected Enterprise 2024: All the takeaways
• Agentic AI without process optimization, orchestration will flop
• On-premises AI enterprise workloads? Infrastructure, budgets starting to align
• The art, ROI and FOMO of 2025 AI budget planning
• Intuit's Enterprise Suite could upend midmarket ERP
• 13 artificial intelligence takeaways from Constellation Research’s AI Forum
• Enterprises leading with AI plan next genAI, agentic AI phases
• With Salesforce push, AI Agents, agentic AI overload looms
• Enterprise security customers conundrum: Can you have both resilience, consolidation?
• Big software deals closing on AWS Marketplace, rival efforts
• Peraton's Cari Bohley: Why internal talent recruiting and retention is critical
• Starbucks lands new CEO from Chipotle: Here’s how digital strategy could change
• Disruption is coming for enterprise software
• Enterprise software vendors shift genAI narrative: 'GenAI is just software'
• The generative AI buildout, overcapacity and what history tells us
• Enterprises start to harvest AI-driven exponential efficiency efforts
• GenAI may be the new UI for enterprise software
• Education tech in turmoil amid genAI: Why consolidation is next
• 14 takeaways from genAI initiatives midway through 2024
• OpenAI and Microsoft: Symbiotic or future frenemies?
• AI infrastructure is the new innovation hotbed with smartphone-like release cadence
• Don't forget the non-technical, human costs to generative AI projects
• GenAI boom eludes enterprise software...for now
• The real reason Windows AI PCs will be interesting
• Copilot, genAI agent implementations are about to get complicated
• Generative AI spending will move beyond the IT budget
• Financial services firms see genAI use cases leading to efficiency boom
• Foundation model debate: Choices, small vs. large, commoditization
• Will demographics mitigate the genAI hit to workers?
• An ode to middle managers
• Enterprise generative AI use cases, applications about to surge
• Multi-cloud computing isn't 'a bunch of separate clouds'
• AX100 interview: How The Joint maps the customer journey as it scales
• Will generative AI make enterprise data centers cool again?
• With Equifax's cloud transformation at finish line, AI scale comes into focus
• Nvidia's uncanny knack for staying ahead
• GenAI trickledown economics: Where the enterprise stands today
• General Motors needs to fix its software issues quickly
• Why customer satisfaction, CX shows diminishing returns
• Supply chain transformation critical as resilience worries stack up
• Themes from the healthcare data, AI, disruption front lines
• 2024 in preview: 11 things in enterprise technology to watch

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.&nbsp; <br>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… Read more

Omar Jacques Omran said innovation is a team sport built on relationships and win-win scenarios that can even bring fierce competitors together to co-innovate.

Omran, a BT150 member, is an entrepreneur and former CTO of Six Flags where he led a transformation that resulted in a $100 million net profit increase over two years.  Before joining Six Flags, Omran was the Vice President of Digital Transformation at Welbilt and the Managing Director of Welbilt’s KitchenConnect brand. Under his leadership, KitchenConnect grew into the largest cloud platform in the foodservice industry, enabling seamless connectivity for smart equipment in restaurants. He also initiated the largest digital alliance in the food service industry.

These industry alliances are notable because ultimately enterprises in various verticals will need to form value chains with co-innovation at the forefront.

Here are some of the takeaways from my chat with Omran:

The mindset for innovation. Omran said that "innovation doesn't start with technology." He said the first part of innovation is being optimistic and believing the best is yet to come and there are opportunities to improve. Perhaps the biggest mindset shift is "having empathy and generosity to knowing you get a multiplier effect by bringing people together."

Bringing teams together means partners, vendors and even competitors when there's a win-win. "By bringing partners together you can go big and faster even if you don't have the biggest budget," said Omran. "And make sure that everybody's going to win, not only you."

Six Flags as an innovation experiment. Omran said in many ways Six Flags and theme parks are small cities with food, services, retail, parking, digital maps and other common services. However, budgets are limited and the goal was to "leverage technology to create a better value for our consumers," he said.

Omran noted that Six Flags roadmap was ambitious and the only way to do it was to create a team and ally with similar companies. With the likes of HCL, Snowflake and Google Cloud, Six Flags was able to deliver cloud and data services, integrate systems and come together to leverage technology across theme park areas including point-of-sale.

Ideation. Omran said Six Flags brought together partners and vendors to come up with ideas to transform the company. These workshops led to kiosks, a new mobile app for parking, maps and theme park services and new point-of-sale systems and AI on the back end.

Relationships. Bringing vendors together revolved around relationships and values that all of the partners were on equal footing and driving wins within their expertise, said Omran. When working with competitors, Omran said it's about co-innovation and driving ideas that will benefit the entire industry and increase the total addressable market. "If you can combine budgets you'll be stronger together and go to market in a bigger way," said Omran. "But first you need trust because everybody is going to be afraid to lose a share of the pie. If you're able to trust then you can get a bigger share of the pie."

More interviews:

• Supernova Award Spotlight: How Singapore's M1 Cloud Transformation Led to Personalized Mobile Plans
• BT150 Spotlight: Centurion Health's Johnny Wu on delivering healthcare in prisons
• BT150 Spotlight: Insight Global's DeWayne Griffin on HR, AI and Humans in the Loop
• BT150 Spotlight: MultiCare Health System's Laurie Wheeler on optimization, change management and healthcare transformation
• BT150 Spotlight: Jewelers Mutual John Kreul on Human-Centric AI, CX, Returns and Future-Proofing
• BT150 member Dr. Jonathan Reichental: How autonomous vehicles could change how cities are designed
• Peraton's Cari Bohley: Why internal talent recruiting and retention is critical
• SuperNova Award interview with Joe Prota: How IBM used Adobe Firefly to speed up ideation and iteration
• BT150's Ashwin Rangan on CIO evolution, technology curves and what it means for genAI deployments
• BT150 Spotlight: Sunitha Ray on the difference between enterprise AI and genAI