OpenAI, Microsoft reach an understanding of something as AI harmony awaits

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

OpenAI and Microsoft put out a joint statement that they've reached a detente and may have raised more questions than they answered. Simply put, the OpenAI and Microsoft relationship is a little more clear but not by much. I'm sure it'll all work out great. 

In a joint statement, the companies said:

"OpenAI and Microsoft have signed a non-binding memorandum of understanding (MOU) for the next phase of our partnership. We are actively working to finalize contractual terms in a definitive agreement. Together, we remain focused on delivering the best AI tools for everyone, grounded in our shared commitment to safety."

Welcome to the week of things that may happen...or not. OpenAI and Microsoft's statement will get a lot of play, but it's not much different than Oracle's massive remaining performance obligation figures which reportedly revolve around OpenAI buying $300 billion in AI compute in 2027. It's an I. O. U. since OpenAI doesn’t have the money...yet. I may buy that compute once I win the Powerball. I already signed the non-binding contract of things that may happen should I become obscenely wealthy in two years.

So now, OpenAI, which apparently is the master of projections for a perfect world, has an understanding that'll it'll reach an understanding with Microsoft.

But seriously, this OpenAI and Microsoft thing is great news. What we do know from another statement is that OpenAI will remain a non-profit that will have funding of more than $100 billion. Yes, these figures are starting to look like their priced in Japanese Yen at this point.

I just feel better that OpenAI and Microsoft are getting along.

• OpenAI vs. Microsoft: Why a breakup could be good
• OpenAI and Microsoft: Symbiotic or future frenemies?

The Public Benefit Corporation (PBC) will continue to oversee the for-profit OpenAI and have an equity stake. The stake tops $100 billion and makes PBC "one of the most well-resourced philanthropic organizations in the world."

To put this PBC funding in perspective, it's worth a Gates Foundation comparison. Bill Gates and Melinda Gates through 2024 have given $60.2 billion to the Gates Foundation, which has paid out $83.3 billion in grants since inception. Warren Buffet has given $43.3 billion to the Gates Foundation from 2006 to 2024. The Gates Foundation has a trust endowment of $77.2 billion exiting 2024.

OpenAI's PBC will have a larger endowment than the Gates Foundation with a key caveat: PBC's funding will be based on OpenAI's valuation and a future business that'll revolve around AGI and domination of the competition. Hmm.

In any case, this non-binding understanding with Microsoft makes the software giant more of an investor. The PBC would theoretically get to do more good as all parties benefit.

A cynic (can you see me raising my hand looking perplexed and possibly jumping up and down) would call this MOU a bit of vapor, but I’m sure glad OpenAI and Microsoft don't have to go nuclear since it's arguably the most lucrative technology partnership in history.

I mean just look at the happiness between these two.

Now Microsoft looks like it will officially be an investor under the new structure even though no details have been provided. The details will be critical:

• How much power will PBC really have?
• What happens when safety and mission collide with profits?
• How will market pressures trade off with what the PBC wants?
• Who will be on the board of the PBC overseeing the push to AGI?
• How transparent is the oversight and governance of OpenAI?
• PBC has a stake of more than $100 billion in OpenAI, but what’s the dilution to existing investors?
• What rights will Microsoft have with its investment?
• Will OpenAI spin off units that won't be under PBC control in the future?

For giggles, I asked ChatGPT to clarify this new OpenAI-Microsoft detente and think through scenarios. After all, since we're playing with a made up understanding with made up numbers, we might as well break out the crystal ball too.

The scenarios boil down to this:

• Mission and capital will be in harmony under this structure. PBC has real veto power over safety, direction and deployment of frontier models. Microsoft has preferred rights, but doesn't dictate roadmap. All is well. I couldn't stop laughing about the odds of this one playing out.
• Investors gain influence and profits trump mission. Microsoft and other investors wind up influencing the PBC. Microsoft is essentially a co-owner. OpenAI benefits from faster commercialization and revenue growth, but has to hear "sell-out" from critics. I can see a PBC board of Larry Ellison, Elon Musk, Sam Altman, Satya Nadella and some token AI ethics professor from Stanford any day now.
• PBC has a lot of authority and OpenAI grows slow. Tensions boil over as OpenAI rivals move faster. It's the good for drama, bad for market capitalization scenario.
• OpenAI starts spinning out parts to focus more on investor-led initiatives. Think OpenAI Labs, OpenAI Enterprise and OpenAI Consumer as a trio of companies.

I’m sure we’ll get to the harmony scenario because in the age of RPO, IOUs and valuations based on SPAC-like made up future revenue figures what could go wrong?

Adobe reports strong Q3, raises outlook

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Adobe reported better-than-expected third quarter earnings and raised its outlook for the rest of the fiscal year.

The company reported third quarter net income of $1.77 billion, or $4.18 a share, on revenue of $5.99 billion, up 11% from a year ago. Non-GAAP earnings were $5.31 a share.

Wall Street was expecting third quarter non-GAAP earnings of $5.18 a share on revenue of $5.91 billion.

Adobe CEO Shantanu Narayen said "AI-influenced" annual recurring revenue topped $5 billion and AI-first ARR topped $250 million. Narayen said Adobe was raising its outlook due to AI product innovation and go-to-market execution.

Narayen said:

"AI represents a tectonic technology shift and presents the biggest opportunity for Adobe in decades. Our strategy to harness AI is focused on infusing it across our category-leading applications to provide more value and delivering innovative new AI-first products. We’ve done a great job executing this strategy by accelerating innovation with a focus on offering greater value to Creative and Marketing Professionals and Business Professionals and Consumers."

The company saw strong subscription growth across its digital media and digital experience units. Remaining Performance Obligations was $20.44 billion exiting the quarter. Adobe's digital media unit delivered revenue of $4.46 billion, up 12% from a year ago. Digital experience revenue was $1.48 billion, up 9%. Digital experience subscription revenue was $1.37 billion, up 11%.

• Adobe launches LLM Optimizer, GenStudio and Firefly updates
• Adobe's AI strategy, monetization 'feels really good right now'
• Adobe's plan: Leverage agentic AI for CX, unify platform

Adobe's quarter didn't include uplift from its latest agentic AI additions. The company, which is facing increased competition from Canva and newly-public Figma, announced general availability of its AI agents for customer experience Sept. 10. Adobe said the new agents, powered by the Adobe Experience Platform Agent Orchestrator, will be able to understand context, plan multi-step actions and refine responses.

The out-of-the-box agents in Adobe Experience Platform include:

• Audience Agent for audience optimization and personalization.
• Journey Agent to create and orchestrate customer journeys across multiple channels.
• Experimentation Agent to leverage performance data and optimize on the fly.
• Data Insights Agent to aggregate signals across an enterprise.
• Site Optimization Agent to manage brand websites and optimize for performance.
• Product Support Agent, which can give answers based on knowledge bases and enterprise data.

As for the outlook, Adobe said fourth quarter revenue will be $6.075 billion to $6.125 billion with non-GAAP earnings of $5.35 a share to $5.40 a share. For fiscal 2025, Adobe projected revenue of $23.65 billion to $23.7 billion with non-GAAP earnings of $20.80 a share to $20.85 a share.

Box launches Box Extract, Box Automate, Box Shield Pro

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Box rolled out new tools to extract data from unstructured content, automate workflows and orchestrate work and layered more AI features in Box Apps.

At the company's BoxWorks conference, CEO Aaron Levie outlined Box Extract, Box Automate and new Box Apps features to address the day that AI agents outnumber people. Levie said:

"Imagine a future where these agents are running autonomously in the background, at scale across an organization. We will have potentially 100 times or more agents in our organization than people, and that's going to be a very different reality of what work looks like."

Levie argued that Box's Intelligent Content Management platform can address the content workflow, processes and governance.

"We believe that the companies that thrive in this AI first era of work will be those that can fully tap into and take advantage of their unstructured data at scale," said Levie. "With AI agents on unstructured data we can streamline production, accelerate critical missions and deliver new products to market even faster."

Box previewed its BoxWorks announcements during its latest earnings conference call. Here's a look at the key announcements.

Box Extract uses AI via Box AI standards and Enhanced Extract Agents to understand documents and extract information. Box Extract can handle multiple formats including PDFs, scans, images and structured data, interpret text, tables, handwriting and bar codes, capture semantic relationships and ensure data quality.

According to Box, Box Extract can improve processes that need contract, invoices, forms and other unstructured content.

Box Automate is a tool to design and manage workflows with a no-code/low-code interface, create AI agents for workflows, route tasks and automate processes via integration with Box Forms, Box Doc, Box Sign and Box Hubs.

• Boxs preps no-code tools, aims for content workflow automation after strong Q2
• Box's master plan: Be the unstructured data enabler of agentic AI

Box Apps will get new functionality to surface insights and trends, filter and surface content views via natural language, manage multiple dashboards and embed apps into third-party platforms.

BoxShield Pro will deliver tools to defend against ransomware attacks, classify sensitive content and analyze threats. BoxShield Pro is a new product built on top of Box Shield, which launched in 2019.

The company said the new offerings will be available later this year.

Cognizant CEO Kumar: Agentic AI will create a reinforcing flywheel of ROI

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Cognizant CEO Ravi Kumar said agentic AI use cases can create a self-funding flywheel for enterprises starting with the software development cycle and moving through other processes.

Speaking at the Goldman Sachs Communacopia + Technology Conference, Kumar laid out a framework for AI agents across multiple vectors. He added that Cognizant is seeing benefits now that 30% of its code is written by machines, up from 18% just a quarter ago.

"There is a unique opportunity to transfer that productivity and share the savings with our clients, especially at a time when interest rates are high, you have a unique opportunity to unlock discretionary," said Kumar, who noted machine-written code can lower the cost of deployment.

Cognizant reported strong second quarter earnings of $1.31 a share on revenue of $5.24 billion, up 8.1% from a year ago. For fiscal 2025, Cognizant is projecting revenue of $20.7 billion to $21.1 billion.

Kumar said these early agentic AI efforts are a multi-year trend that's just starting. "CIOs across the world are not seeing their budgets are going to be lower than before because of productivity. They're either keeping the budgets flat or they're actually increasing the budgets for the upcoming AI spend, which is happening. So what CIOs are doing is they're taking the savings, underwriting it for innovation, which is powered by agentic cycles," said Kumar.

Constellation Research CEO R "Ray" Wang argued in a research report that enterprises need to rethink old models in enable AI and shed tech debt. Wang also recently examined AI exponentials and their potential.

• The road to AI Exponential will be bumpy

The Cognizant CEO broke down the agentic AI flywheel like this.

Vector 1: Software Development Productivity

• Apply AI to software cycles to increase productivity.
• Savings from this productivity are shared with clients or reinvested.
• These savings fund innovation projects powered by agentic AI.

Kumar noted that the first vector is really about consolidating platforms and eliminating tech debt (to some extent). Vector 1 isn't characterized by net new IT spending, but making existing spend more productive. "CIOs are saying give me savings to use for AI. If the macro changes that will accelerate the CapEx spend on agentic," said Kumar.

Vector 2: Migration to the Agentic layer

• Move business logic from traditional SaaS layers into an agentic layer (either SaaS-native or custom).
• Agents integrate with human capital + structured/unstructured data, creating larger surface areas of opportunity.
• Compared to software cycles, agentic cycles have a multiplier effect, since each employee may work with multiple agents.
• Development is outcome- and behavior-driven, iterative, and requires ongoing supervision, unlike traditional maintenance.

Kumar said:

"In agentic tech, you scope for outcomes, you design for behavior, you do iterative development because agents actually improve over time. They change their behavior. And then after you scale them, you supervise them. You don't just keep your lights on. And supervising is a much bigger task than maintaining software."

However, vector 2 will take time to develop. "There will be transition of deterministic logic sitting in SaaS layers into the agentic layer. There'll be new Agentic layers built. It could be on existing software stacks. It could be direct with frontier model companies like OpenAI and Anthropic, who also want to go direct to the enterprise, and they would use us to get there. That hockey stick is on the way," said Kumar.

• Pondering the future of enterprise software
• Lessons from early AI agent efforts so far
• Every vendor wants to be your AI agent orchestrator: Here's how you pick

Vector 3: Unlocking New Labor Pools

• Combining agentic capital and human capital can create new outsourcing cycles.
• Example: customer care was transformed into a 65–35 agentic-to-human model, after which a client asked Cognizant to run the entire function.
• This extends Cognizant's market beyond technology services into operations of enterprises, massively expanding the total addressable spend.

Kumar said:

"Agentic layer is going to be a multiplier to the software layer. So it's a much bigger growth opportunity. And then you're going to see unlock of new labor pools. And those labor pools are not related to technology. Those labor pools are related to operations of enterprises, and that total addressable spend is a much bigger spend than what we saw before."

Add it up and agentic AI becomes a self-reinforcing loop, according to Kumar.

1. Software-led productivity gains (vector 1) generate cost savings.
2. Those savings are reallocated into agentic development cycles (vector 2).
3. Agentic cycles deliver further cost savings, better experiences, and eventually new products and services.
4. This unlocks new labor pools and operational outsourcing opportunities (vector 3).
5. Operations-led transformation expands Cognizant's addressable market (especially in BPO, now its fastest-growing service line).
6. Expanded spend fuels more adoption and reinvestment in agentic cycles — creating a growth flywheel.

Supernova 2025: How Jeitto uses alternative data in Brazil for credit decisions

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Alex Franco, Chief Risk Officer and Chief Technology Officer at Jeitto, artificial intelligence and alternative data can democratize access to credit at a faster pace.

Franco, a Supernova Award 2025 finalist, recently outlined Jeitto's mission and approach to technology. Jeitto primarily operates in Brazil and provides credit to more than 11 million customers. Many of those customers are underserved by banks.

Jeitto has automated decision workflows through its mobile app and AI-led processes. Since deploying Provenir’s AI Decisioning Platform, Jeitto has seen a 20% reduction in defaults on the Jeitto Loan, grown its customer base and recorded a 10% increase in its credit approval rate. Jeitto's credit assessment cycle time has moved from 1.5 minutes per application to 30 seconds.

We caught up with Franco to talk shop. Here's a look at the key themes.

Target market. Franco said Jeitto is focused on Brazil's underserved population "that earns low income, that has a lot of difficulty to get access to credit in Brazil."

Alternative data. Jeitto leverages AI and alternative data for credit decisions. Franco said: "Since 2014 Jeitto has been working on AI and alternative data to provide credit to the population in Brazil." Key data points include.

• Cell phone data, a key factor in credit decisions.
• Fiscal data retrieved through the customer's fiscal ID in Brazil
• Customer behavior data.

Strategic expansion. Franco said Jeitto has 13 million consumers in its database and is now looking to add new services and loans to become a broader financial platform.

Technology strategy. Franco said Jeitto's stack revolves around combining best-in-class platforms to leverage AI and intelligence. Core functions are those technologies that affect the customer experience and long-term value.

Jeitto's platform connects fraud scores, identity checks and device validation, integrating multiple layers of fraud detection into decisioning workflows to mitigate threats at application screening, including synthetic fraud, impersonation and mule indicators. This eliminates siloed environments between credit and fraud risk teams, to ensure holistic, end-to-end decisioning with a complete view of customers across the entire lifecycle.

Microsoft 365 launches role-based Copilots

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Microsoft announced a set of Copilots for sales, service and finance in a move that brings role-based assistants to Microsoft 365 Copilot.

The role-based Copilots will be available in preview for Microsoft 365 Copilot customers in October via the Copilot Agent Store.

Microsoft's offering is the latest in a trend of copilots and AI agents aimed at specific roles and processes.

With the Copilots for Sales, sellers can leverage AI within their usual productivity tools. Ditto for service pros and finance teams. Directions on Microsoft analyst Mary Jo Foley noted that the role-based Copilots are part of a rebrand.

• Microsoft delivers strong Q4, Azure delivers $75 billion in annual revenue
• Microsoft wants to be your agentic AI developer stack
• Microsoft supports Google Cloud's Agent2Agent standard
• Microsoft raises prices for Dynamics 365 Business Central
• Microsoft: Human, AI agent ratios will be critical to success as new roles emerge

In a blog post, Microsoft pitched "Frontier Firms" that put AI at the center of customers experience, productivity and processes.

Constellation Research CEO R “Ray” Wang argued in a research report that enterprises need to rethink old models in enable AI and shed tech debt. Wang also recently examined AI exponentials and their potential.

• The road to AI Exponential will be bumpy

For these role-based Copilots to work, Microsoft is connecting them to outside systems. For sales, Copilot connects to Microsoft's Dynamics 365 as well as Salesforce and other CRM systems. Finance connects to Dynamics 365 as well as SAP and other ERP systems.

• Pondering the future of enterprise software
• Lessons from early AI agent efforts so far
• Every vendor wants to be your AI agent orchestrator: Here's how you pick

Constellation Research analyst Holger Mueller said:

"For the first wave of agents to keep a role focus needs to be on a valid True North. And efficiency gains from agents will benefit any role. The prize for enterprises though is not in efficiency - but effectiveness: Doing the right thing is the key design challenge in the agentic era. Agents are not bound to human roles and unleashing the next level of enterprise effectiveness is really the game enterprises must play and win. Role based agents can only be the start. Otherwise role-based agents can further cement up the 'efficiency trap' (which is missing the effectiveness exit)."

ServiceNow launches Zurich release, inserts process, task mining into AI agent workflows

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

ServiceNow launched its Zurich release of its platform with tools to build AI apps and agents more easily, attach identities to digital workers and integrate process and task mining into agentic workflows.

With ServiceNow's previous releases--Yokohama and Xanadu--the company began rolling out AI agents throughout its platform. The Zurich release is aimed at providing more agentic AI tools to developers and scaling agents automation.

In addition, ServiceNow is bringing process mining and task mining to that agentic AI pipeline. As previously noted, process is often overlooked in agentic AI plans and that's a strategic mistake for enterprises.

ServiceNow acquired UltimateSuite in late 2023 to build out its native process and task mining capabilities.

• ServiceNow offers US government discounts as high as 70% on ITSM
• ServiceNow posts strong Q2 as McDermott reiterates CRM ambition

Kush Panchbhai, Senior Vice President of AI Platform, Zurich is an effort to give customers the tools to "pivot from legacy automations to proactive automations across all of the workspace" and structured and unstructured data.

Process optimization is also critical. Zurich will include task mining to observe what humans are actually doing in an enterprise. Combined with process mining, Panchbhai said Zurich brings the ability to optimize "how work is flowing in an enterprise."

The ability to identify inefficiencies via process and task mining is critical because those insights "are then food for our AI agents" to automate with streamlined processes, he said.

"You want to make sure that all the inefficiencies the customers have today can be solved by agentic scenarios. That's why we are launching agentic playbooks," said Panchbhai.

To Panchbhai, process mining is "step zero" to building AI agents. ServiceNow has more than 20 years’ worth of workflow and process automation data that developers can use to create adaptive AI agents. He said:

"When you use these mining capabilities, you essentially find lot of bottlenecks and it can take days to get from one step to another step. Most of the time, process mining doesn't reveal an optimized map. It's like spaghetti when we run process mining across different use cases. We analyzed all that spaghetti and returned recommendations so we can give you tools to fix inefficiencies with a click of a button. That's why I think about this as step zero in building an agent."

Developer tools

Jithin Bhasker, Group Vice President and GM of Creator Workflows and App Engine at ServiceNow, said the Zurich additions recognize that "in the next two years, a third of every application will be refactored and rewritten to be able to support data and AI readiness."

Bhasker said that once applications are revamped for agentic AI workflows will be optimized and tweaked using no code and low code tools. "This will effectively drive a massive amount of customer AI applications and agents being built," said Bhasker, who said software will be built with natural language and simple prompts.

Add it up and ServiceNow is aiming to be the platform that is that tweener between building and buying enterprise software. You buy the platform and then build AI applications and agents with governance, integration and security.

The vision for ServiceNow rhymes with the strategy for Salesforce and a bevy of other SaaS players. Give every employee a digital coworker to boost productivity.

Key enhancements to Zurich include:

• Build Agent, which includes conversational development tools so business experts can built apps with generative AI and sandboxes. "It's all about how you automate and accelerate the entire lifecycle from idea to an app in a minute," said Bhasker.
• Built-in process mining. Bhasker said process and task mining is baked into Build Agent to recommend process flows and automatically provide optimization insights.
• Developer Sandbox, a dedicated environment for agentic app development.
• Adaptive Agents, which are self-optimizing applications to deliver outcomes.
• Machine Identity Console with governance enhancements via AI to ensure compliance.

Amanda Grady, Vice President and GM of AI Platform Security, said the upcoming proliferation of AI agents will require a machine identity console.

Grady said AI agents are a new type of identity more akin to a service manager. The Machine Identity Console in Zurich will assign identities to AI agents and identify high-risk integrations and security improvements.

The Machine Identity Console includes the following:

• Centralized visibility of all inbound API integrations.
• The ability to identify high-risk service account identities with preventative actions.
• Improved security with recommendations with clear steps.

Grady said ServiceNow is also adding features to Vault Console to know, protect and monitor data. ServiceNow Vault includes a guided experience for sensitive data auto-classification and protection, streamlined security tools and audit and compliance management.

Hitachi Digital Services launches HARC Agents, AI agent library, management system

Larry Dignan

Editor in Chief of Constellation Insights
Constellation Research

Larry Dignan is Editor in Chief of Constellation Insights at Constellation Research, where he leads editorial coverage focused on enterprise technology, digital transformation, and emerging trends shaping the future of business. He oversees research-driven news, analysis, interviews, and event coverage designed to help technology buyers and vendors navigate complex markets with clarity and context. ...

Read more

Hitachi Digital Services launched a library of more than 200 pre-built AI agents across industries and use cases as well as an Agent Management System that aims to provide a single pane of glass to manage multiple agentic AI platforms.

The new library and agent management system landed as Hitachi Digital Services unveiled Hitachi Application Reliability Center (HARC) Agents.

Hitachi Digital Services' launch highlights a few notable trends:

• Integrators are in a strong position to provide agentic AI given they touch multiple systems and think in terms of process.
• Operations technology is becoming intertwined with IT.
• And enterprises are focused on value for specific use cases.

For Hitachi Digital Services, the launch is a follow-up to its May analyst day where it broadly outlined its strategy, customer use cases and its AI platform and software. Hitachi Digital Services added its Agent Library and Agent Management System to its HARC Agents platform, which also includes R202.a, a framework for defining and developing enterprise AI deployments, and HARC for AI, a set of professional and managed services to operationalize AI systems.

More on Hitachi Digital Services:

• Hitachi Digital Services CEO Lvin on AI transformation, operations technology and use cases
• Hitachi Digital Services: A deep dive on what it does, IT, OT, AI strategy (See PDF)
• Constellation ShortList™ Innovation Services and Engineering

According to Hitachi Digital Services, the HARC Agents stack can reduce time to value for AI agents by 30%. Roger Lvin, CEO of Hitachi Digital Services, said the company is trying to address a key pain point for enterprises. "Too many technology partners are content to run pilots, chase headlines, and talk theory," said Lvin, noting that enterprises need "operationalized AI" that drive returns.

Hitachi Digital Services said its Agent Library is focused on industrial AI with vertical-specific use cases and AI for operations, engineering, analytics, security and cloud. The company added that it will add new agents continuously.

The Agent Management System (AMS) from Hitachi Digital Services is another tool worth watching. With AMS, Hitachi Digital Services is looking to manage various agentic platforms such as Microsoft Azure Copilot Studio, Google Cloud's Agentspace, Ema, Lyzr and others holistically.

Bottom line: Enterprises are being pitched multiple AI agent platforms, but are likely going to look for one neutral point to operate what's going to be a sprawling heterogenous agentic AI landscape.

• Pondering the future of enterprise software
• Lessons from early AI agent efforts so far
• Every vendor wants to be your AI agent orchestrator: Here's how you pick