AI spending is surging – yet the return on investment remains elusive. According to BCG, companies expect to double their AI budgets this year, with 72% of CEOs now leading AI strategy directly. Yet Deloitte finds that only 25% of organizations have moved even 40% of their AI pilots into production. McKinsey adds a sharper warning: nearly two-thirds of enterprises have experimented with AI agents, but fewer than 10% have scaled them to tangible value with eight in ten citing data limitations as the primary barrier.
The message for boards is clear: funding AI as a technology program is no longer enough. The next wave of enterprise value won’t come from accumulating pilots or deploying more agents. It will come from redesigning how work operates – with process discipline, governed orchestration, and measurable outcomes at the center.
This point of view, authored by Amit Bhutani, Corporate Vice President – Agentic Business Automation at Persistent, makes the strategic case for convergence: low-code for speed, Agentic AI for reasoning, and orchestration for trust. It offers CEOs and board members a practical playbook for scaling AI, not through more experimentation, but through process-first design, data readiness, and controlled autonomy.
In this POV, you’ll learn:
- Why process-first design is the real differentiator and why deploying agents into broken workflows only amplifies dysfunction
- How orchestration has emerged as the control plane for enterprise autonomy, governing agent hand-offs, escalation logic, and policy enforcement
- A four-step board-level playbook for scaling Agentic AI from process intelligence to reusable patterns and outcome discipline
- Where low-code and Agentic AI converge to accelerate enterprise outcomes across claims, procurement, onboarding, and beyond
