A notable shift is underway across the agency and consulting landscape. Over the past few years, major services firms have begun acquiring AI and analytics product companies at an accelerating pace. Accenture’s acquisition of Faculty and Publicis’ purchase of Adge AI are recent examples, but they are part of a broader pattern that includes WPP’s acquisition of Satalia, Stagwell’s purchase of the Apollo Program insights platform, and KPMG’s acquisition of Metaphor’s data platform technology.

This signals a meaningful evolution in the services business model.

Part of what is driving this shift is financial. Product revenues, if firms can credibly position them as scalable platforms rather than thin wrappers around services, tend to carry higher margins and stronger long-term value than traditional services work.

At the same time, agencies and consultancies are under increasing pressure to articulate a compelling AI strategy. As AI begins to compress delivery effort and reduce reliance on billable hours, firms are looking for ways to reposition themselves beyond labor-based models and toward more technology-driven offerings.

For decades, agencies and consulting firms have operated as people-driven organizations. Their core asset has been expertise delivered through projects, retainers, and billable hours. AI is beginning to challenge that model. As AI accelerates analysis, coding, and content creation, the human labor required to deliver many services declines, creating margin pressure for firms whose revenue historically scaled with headcount.

Owning proprietary software offers a way to counter that pressure. Instead of relying solely on labor-based revenue, firms can wrap services around proprietary technology. AI platforms, predictive analytics engines, and optimization tools provide repeatable assets that can be deployed across multiple clients. The combination of services and software allows firms to scale delivery more efficiently while creating differentiated intellectual property.

Another motivation is strategic control over the decision layer of the marketing and digital stack. The companies being acquired tend to sit close to where decisions are made: predictive measurement platforms, creative optimization tools, data orchestration systems, and AI planning engines. These tools influence how budgets are allocated, how creative is produced, and how performance is evaluated. When the same firm both operates campaigns and owns the system that determines success, it occupies a powerful position in the value chain.

None of this is inherently problematic. In some cases it may even accelerate innovation. But enterprise buyers should approach these offerings with clear eyes.

The first issue is independence. Agencies and consultancies were never fully neutral advisors. Most have long pushed preferred partner ecosystems, often reflecting commercial relationships or internal expertise. But there was still a meaningful degree of choice. Clients could select among competing platforms while the service provider recommended and integrated them.

When firms begin owning the software used to plan, optimize, and measure marketing performance, that dynamic shifts further. The recommendation layer collapses into the delivery layer. A firm that designs a campaign, runs the campaign, and measures the campaign through its own platform is effectively grading its own homework, particularly in areas such as attribution, optimization, and predictive measurement.

Another concern is lock-in. When a services firm embeds its own software into core workflows, switching partners becomes far more difficult. Clients are no longer replacing only a service provider; they may also need to replace the analytics engine, data models, and decision logic underlying their marketing operations. What begins as a services engagement can quietly evolve into a deeply embedded technology dependency.

Historical precedent also suggests caution. Services firms have generally struggled to build and sustain successful software products because product development requires a very different operating discipline. There are a few notable exceptions, but they are rare and instructive. 37signals, originally a web design consultancy, built Basecamp to manage client work and ultimately evolved into a software company known for Basecamp, HEY, and Ruby on Rails. Mailchimp began as a side project inside the Rocket Science Group web agency before growing into one of the world’s largest marketing automation platforms and being acquired by Intuit for roughly $12 billion. Hootsuite started as an internal dashboard within the digital agency Invoke Media before being spun out into a standalone company and category platform. These examples demonstrate that successful products can emerge from services environments, but they remain the exception rather than the rule.

For enterprise marketing and digital leaders, the safest approach is to treat these offerings as both a service relationship and a software procurement decision. Buyers should ensure they have clear answers to several questions before committing to a platform owned by a services firm. Who owns the data generated by the system? Can models and insights be exported if the relationship ends? Is the measurement methodology transparent and auditable? And could the platform realistically stand on its own as a product independent of the consulting engagement?

And if you worry, like RSG does, about “consultingware,” then you would reasonably ask to see a real roadmap delivered by a real product manager.  And you would be able to test-drive a real installation to ferret out where the platform is abstracted like real software and where….it’s not.

The broader trend reflects a deeper convergence in the industry. Software companies are expanding into services to help clients deploy increasingly complex platforms, while services firms are moving into products to protect margins and create proprietary IP. AI is accelerating both directions at once.

As a result, the traditional boundaries between agencies, consultancies, and software vendors are beginning to blur.

For enterprise buyers, that means vendor evaluation must evolve as well. When a services firm presents a proprietary AI platform, it should be assessed not only as a consulting capability but as a long-term technology component of the stack because the platform may remain long after the consulting engagement ends.

We’ve always said there’s fifty ways to leave your services firm, but only one way to leave your platform vendor, and it’s always painful.

As the lines between services and software continue to blur, enterprise teams need a clear framework for evaluating both. RSG supports organizations in assessing emerging platforms within the context of their broader architecture. Reach out if you're looking for some help.