AI platforms are becoming the secret weapon for IT service providers looking to stand out in a crowded market.
In addition to traditional consulting and systems integration, partners are rolling out "productized" AI platforms that promise faster deployments and more concrete deliverables than open-ended service engagements.
The term "platform" covers a lot of ground in this context — everything from ready-made AI agents and pre-trained models to code generators, AI accelerators, and industry-specific workflows. But the common thread is repeatability: These platforms give partners standardized offerings they can deploy multiple times, rather than building everything from scratch for each customer.
Chris Barbin, founder and CEO of Tercera, an investment and advisory firm that specializes in IT services, said his company has spoken with about 800 tech services businesses over the last five years. Nearly all of them go to market with some form of accelerator or packaged IP, he noted in an email interview.
The trend has intensified in the last 18 months.
"We're seeing more substantial productization of services, and almost every firm is developing packaged agentic solutions that are specific to the verticals or ecosystems/platforms they serve," Barbin said.
That pattern surfaced in recent earnings calls, where IT executives have highlighted platforms as a crucial part of their AI strategies.
At Cognizant, CEO Ravi Kumar S cited platforms as a component of the professional services company's "AI builder" strategy.
"Our investments in platforms, intellectual property, partnerships, and in upskilling of people are evolving Cognizant into an AI builder, capable of scaling agentic AI across the enterprise," he said during an Oct. 29 earnings call.
Kumar pointed to Flowsource, an AI-based software engineering platform, as an example of a Cognizant platform.
"Flowsource is now being used at over 70 clients with an additional 120 in the pipeline," he said, noting that the platform integrates generative AI and agentic AI across the software development lifecycle.
Hitachi Digital Services also employs a platform-centric approach to AI, according to Premkumar Balasubramanian, the company's CTO. That approach builds on the company's Hitachi Application Reliability Center Agents, an enterprise agentic AI platform that launched in September.
In an email statement, Balasubramanian described the platform as a unified, agentic operating framework that integrates governance, operational reliability, a reusable Agent Library, and an Agent Management System.
Balasubramanian cited "accelerated time to impact" as one AI platform advantage, noting that pre-built agents and modular architecture reduce deployment times by up to 30%.
In addition, Distyl AI, an AI integration startup with a $1.8 billion valuation, has integrated its Distillery AI platform into the company's core offering, which also includes engineering services and AI research. The platform transforms customers’ organizational knowledge into AI-driven workflows.
Varied approaches, varied sophistication
AI platforms can help IT service companies stand out, but providers must demonstrate value.
"Coming in with real IP that demonstrably speeds results and lowers risk is definitely a differentiator for firms, especially in the hype-filled and very crowded AI space," Barbin said. "The key, though, is proving how it makes a difference. A lot of firms we see are putting pretty wrappers around basic LLM models and calling it a platform."
That type of platform can backfire, especially with sophisticated customers, he said.
Barbin said larger, more sophisticated and well-funded companies are building full platforms, while nearly all AI-native firms are also developing legitimate platforms. Few traditional service providers, however, have the "software DNA to create, market and maintain true products," he added.
The drive to develop such platforms is an AI-era take on partners' longstanding urge to productize services. In the 1980s and 1990s, consultancies and systems integrators offered customers software modules that could be customized to meet their requirements. That method came to be known as semi-custom software, in contrast to completely off-the-shelf applications. Semi-custom offerings would provide perhaps 80% of a client's core functionality, with the consultant or integrator custom-coding the last 20%.
IT services executives said today's AI platforms harken to the earlier days of semi-custom software, but with some key differences.
Balasubramanian said the 80-20 enterprise software delivery approach of past years looks different now amid the rise of agentic platforms. He said the ratio has now shifted so that 30% to 50% of the deliverable is standard — pre-built agents and frameworks, for instance — and 50% to 70% is custom.
The increased emphasis on the custom component reflects "the need to train models on customer data and ensure accuracy, reliability, and governance," he said.
A recurring pattern
Barbin has also observed the recurring semi-custom pattern.
"Like a lot of things in the AI era, we’re seeing a similar pattern but with different challenges and opportunities," he said.
One key difference is that AI offerings yield non-deterministic results. That's a departure from traditional software, where the same input consistently generates the same result.
With AI results, "you may not get the same answer every time," Barbin said. "This can be a problem in enterprise applications, and it’s one of the reasons companies struggle to get out of pilot mode."
Additionally, the speed and scale at which companies can customize systems are another key difference with AI platforms. Customization can be automated with co-pilots, agents, and also through model fine-tuning and curated data sets, Barbin said.
While IT service providers assemble platforms and adjust the ratios, customers are looking for what Kumar described as AI "machines." Platforms provide a means to deliver them.
"Our clients are not saying, 'Come in with your capability,'" he said. "They're saying, 'Come in with your machine,' which means you have to actually have the platforms."
