The non-AI work that will set enterprises up for agentic AI success

Everywhere you look, AI is making headlines—new models, new breakthroughs, endless hype. But the next leap isn’t just smarter models, it’s agentic AI: AI that doesn’t just generate answers, but takes action, makes decisions, and uses tools to get things done.

An emerging theme is that the success of AI in the enterprise depends less on the performance of the model itself and more on the foundations around it. Without the right environment, even the most advanced AI agents will stall at proof of concept. In fact, a recent MIT study went viral, revealing that 95% of generative AI implementations in enterprises fail to deliver measurable impact due to flawed integration with existing workflows, not because the AI tools malfunction.

The organizations that win won’t be the ones with the flashiest AI models. They’ll be the ones that master orchestration, governance, and change management. In other words, the non-AI work is what will set enterprises up for success, providing the foundations that turn AI into real business value and keep them ahead in the market for the next decade.

Six foundations executives often miss when implementing AI

These insights are grounded in our experience with customers deploying agentic AI. They reflect common patterns that determine whether agentic AI delivers real impact or gets stuck in early trials.

1. Process intelligence, design, and re-engineering

Most enterprise processes were not built with AI agents in mind. They were designed for people or for deterministic automation. To realize value, leaders must rethink processes for a “mixed workforce” of AI agents, automations, and people. Capabilities like process intelligence can pinpoint inefficiencies and help redesign workflows.

Where should judgment be reserved for people? Where can agents and automation accelerate execution? Getting this design right is where orchestration begins.

Related read: why AI agents need intelligent document processing

2. Agentic orchestration at the core

Agentic orchestration is the connective tissue. Without it, you have a collection of siloed AI agents, systems, tools, and teams. With it, you have a coordinated system of people, automations, and AI agents working together across end-to-end processes. Orchestration ensures execution is reliable, governed, and measurable. It’s the catalyst for turning AI potential into real business impact.

Get the playbook: The definitive guide to agentic orchestration

3. Data infrastructure and quality

An AI agent is only as good as the data it runs on. Clean, reliable, and well-governed data ensures decisions are accurate and outputs are trustworthy. In our experience, organizations that invest early in data see higher adoption and fewer errors. Investing in data quality is not glamorous, but it is one of the most decisive factors in whether agents succeed or fail.

4. Governance and security

High-stakes decisions require clear governance: who can act, what they can do, and how decisions are audited. Organizations often underestimate risk from agent sprawl, where multiple AI agents overlap or conflict.

In our work with clients, implementing role-based access, automating logging, and compliance checkpoints have prevented costly errors and built trust with stakeholders.

5. Change management and culture

Agentic AI transforms how work gets done, so cultural readiness is essential. Leaders should communicate goals clearly, demonstrate AI as a partner rather than a replacement, and involve teams in shaping new workflows. For example, we see clients running workshops where employees co-design agent-assisted processes, which increases buy-in and reduces resistance.

6. User training and enablement

Even with great processes and governance, adoption depends on people. Training employees to understand, trust, and collaborate with AI agents is key. When people know how to work with AI, and where their judgment is critical, they stop seeing it as competition and start seeing it as an advantage. In practice, training, workshops, and internal AI “champions” help teams move from skepticism to confident adoption.

Dive deeper...Teaming up with AI: how agents will fuel enterprise transformation and reshape work

The bottom line

Agentic AI is transformative. But agentic AI alone will not deliver enterprise-scale impact. Change management, process design, governance, data, training, and orchestration are what turn experimentation into measurable results.

In the end, your AI is only as strong as the non-AI foundations that surround it.

And it is those foundations, not the hype, that will define which leaders succeed in the age of agentic AI.

Download "The Definitive Guide to Agentic Orchestration" today.