Across every industry, AI is pushing enterprises to rethink how they deliver value in pursuit of better customer experiences, higher productivity, and stronger business results. In consulting, our role has always been to help organizations redesign how they operate. So, when AI is fundamentally changing how work gets done across every sector, the impact on our profession is especially profound.

As the nature of work changes, consulting will increasingly become a combination of people plus software — a lot of software — delivered through intelligent agents and platforms that can scale far beyond traditional project work. Think of it as “services as software.”

AI is not just a tool or a large language model license you hand to employees and hope for the best. Real impact and return on investment happen only when it is embedded into core systems, governed with guardrails, and managed by people who understand how to apply it.

Take software engineering as an example. Despite all the noise, demand for engineers continues to grow, but the role itself is changing. The modern engineer needs to understand context engineering, know how to vectorize datasets, and build guardrails into non-deterministic AI systems. Those capabilities look very different from what the industry required even a few years ago. And as this shift continues, companies will need to reskill their workforces quickly to remain competitive.

As the only global consultancy embedded within a major technology company, we’re living and breathing this AI-driven moment firsthand. Unlike most traditional consulting firms, we are building AI technology, applying it across the IBM enterprise, and helping hundreds of organizations navigate their own AI transformations, all at the same time.

Because we are building and deploying AI technologies ourselves, we understand that enterprise transformation never relies on a single solution. We’re proud to work across a broad ecosystem of partners to integrate the AI agents, models, hardware, and other technologies that best support each client’s strategy.

We know this because we’ve done it ourselves. Starting in 2023, IBM embedded AI across its operations to significantly boost enterprise productivity, analyzing nearly 400 workflows and reinventing over 100 so far with governance frameworks and global workforce training. This effort has generated $4.5 billion in productivity gains. Few enterprise organizations can say they implemented AI at this level across their own operations, but more importantly, it gave us something even more valuable than the savings. We learned what works when AI becomes core to an enterprise, and we now bring those tested methods into every client engagement.

Now, as companies deploy thousands of AI agents to realize these types of results, a central place where those agents can run, improve, and be managed across the business becomes critical. Gartner has recently coined the term “Agent Management Platform,” to explain this concept. Two years ago, we built IBM Consulting Advantage as our internal Agent Management Platform, and earlier this year we announced IBM Enterprise Advantage as a service to help clients build and scale their own Agent Management Platforms.

For instance:

Our consultants work alongside over 3,000 digital assistants and agents that reduce tedious work and accelerate delivery so they can focus on the decisions and strategy that truly require human expertise. Not all our consultants are engineers by trade, but with IBM Consulting Advantage they are empowered to build agents tailored to each engagement.

We’re now bringing that same approach to our clients through IBM Enterprise Advantage, helping enterprises design and operate their own Agent Management Platforms so they can build, govern, and scale AI agents across the business.

• Pearson, a global lifelong learning company, is building a custom AI-powered platform that combines its expertise in learning and skills development with agentic assistants to transform workforce training and decision making across the enterprise.
• A global manufacturer is implementing its generative AI strategy by identifying high-value use cases, testing targeted prototypes, and aligning leadership around a scalable, platform-first approach. The client is now deploying AI assistants across multiple technologies in a secure, governed environment designed to expand AI enterprise-wide.

The nature of work is changing and consulting must adapt to meet these needs. Firms that hold on to traditional delivery models will struggle, but those willing to redesign how expertise is delivered and combine human judgment with intelligent systems will define the next era.