Despite what you may have read in the media, consulting is not being entirely consumed by artificial intelligence. Yes, the economic paradox of professional services in the AI computing era is that business and technology consultants can use AI-powered delivery platforms to do more work at lower cost. That puts pressure on service provider margins, reduces the need for more headcount, and forces a reconciliation between what enterprise buyers need and what service providers have historically offered.

Meanwhile, CIOs are drowning in AI consulting pitches, from management consulting and Big Four accounting providers promising transformation magic to boutique players claiming AI-native superiority. The noise is deafening and the stakes couldn’t be higher, as every company must reinvent its processes and business model in the AI computing era.

As I take on responsibility for the Forrester Wave™ covering AI consulting services in 2026, and as part of a services analysis team with decades of experience with management consultancies and technology service providers, it’s a good time to state some positions. Providers will have to:

  • Reprice services, because they can do more work at lower cost. This is the short-term effect. Service providers have been through this before in the transition to offshore labor arbitrage and cloud computing. They will do it again, automating more work, establishing deeper co-innovation with alliance partners, and building more assets to improve services and outcomes. They will alter their staffing structures, invest more in platforms, and change their pricing and risk models, including more value-based and shared-risk commercial models. They will also charge explicitly for or bundle in the cost of their assets as part of the new commercial value proposition.
  • Invest more in alliance relationships and co-innovation capabilities. AI consulting service providers have expanded their relationships with hyperscalers, software giants, data platform builders, hardware OEMs, and now NVIDIA. This allows them to get early access to technology, build new solution architectures, (presumably) learn how the technology works before taking it to clients, and take advantage of tech providers’ subsidized delivery dollars. Together with the AI technical service providers, the AI consulting service providers have joined an expanded AI computing ecosystem as solution orchestrators.
  • Build practices to address an expanding array of AI scenarios. We are in the early years of a 15-year transition to AI-powered business. The scenarios for AI-powered business continue to expand. Most scenarios today have focused on internal operating models and technology readiness. The scenarios of tomorrow will focus on customer engagement and products and services that generate revenue. Firms will turn to consulting services for help designing and migrating to AI + human business processes, establishing AI-native business and customer engagement models, and building new roles in AI-powered value chains.
  • Rethink their hiring, development, and organizational models. The death of the pyramid has been pundit fodder for a decade. New structures are proposed every day: diamond-shaped as AI takes over entry-level work, podlike as AI + human delivery shares the load between people and AI machinery, and so on. New entrants into AI business consulting are bringing AI-first value propositions to consulting services and will put pressure on the major consultancies to revamp their approaches. Consultancies still need a talent pipeline to develop the next generation of expertise and establish deeper client relationships, but they also need an expanded portfolio of baseline skills to develop new industry, technical, and client knowledge; build platforms for delivery and operations; and invest in next-generation AI computing architectures.
  • Modify their economic models to share more risk. Consultancies have gotten a free ride on risk, using the motivation of expertise and customer satisfaction as their guideposts for success. Nobody blacklisted a consultancy for giving them bad advice — they just didn’t hire them again. We see this changing. Management consultancies have already moved toward putting their fees at risk (using outcome-based pricing, for example). We see this expanding as enterprises negotiate with their AI consulting service providers to put some skin in the game — and be compensated for taking on that risk.
  • Put their proprietary knowledge and expertise to work. What do AI consulting service providers bring if not proprietary knowledge and expertise? One of the lessons the major consulting providers have already learned is that their proprietary industry, domain, data, knowledge, and code libraries are valuable assets that turn generic foundation models into decent agentic applications. They will invest much more in proprietary knowledge and build offerings and services around that.

All this speaks to a healthy, if different, AI consulting services ecosystem ahead. If you are a Forrester client seeking counsel on AI consulting services, please reach out. If you are an AI consulting service provider, I’m happy to learn more about your practices, your assets, your customers, and your commercial approach to helping clients.