Tredence Launches Strategic AI Playbook to Help Enterprises Move Past the Pilot Trap
Most AI deployments today get stuck somewhere between proof of concept and pilot purgatory. Tredence, a data science and AI consultancy, wants to change that—and fast. The company just released its Agentic AI Playbook, a strategic guide aimed at Chief Data & Analytics Officers (CDAOs) and AI leaders looking to scale artificial intelligence beyond experiments and into enterprise-wide operations.
Rather than another report chasing the usual suspects—LLMs, data lakes, generative use cases—the playbook focuses on something more structural and arguably more pressing: the organizational redesign needed when AI agents start making real decisions. In short, Tredence says it’s time to stop tinkering and start re-architecting.
From Tactical to Transformational
“The biggest risk with AI isn’t hallucination—it’s stagnation,” said Tredence CTO and Co-founder Sumit Mehra. “Companies are still scaling strategy through use case pilots when they need to be redesigning their orgs for a future where humans and machines act as decision-making peers.”
That provocative stance anchors the playbook’s core thesis: AI isn’t just a technology shift; it’s an operating model shift. And most organizations, Tredence argues, are still structured for the pre-agentic era—when humans made all the decisions and software merely assisted.
Instead of framing AI as a bolt-on tool or productivity boost, Tredence urges executives to think in terms of co-intelligence—an operating model where AI agents and humans collaborate on decisions in real time, across functions.
The Five Lenses of Agentic AI
The Agentic AI Playbook is built around five strategic lenses:
- Business Value Realization
Focuses on converting AI investments into real ROI—not just through automation, but by sustaining stakeholder engagement over time. - Human + AI Co-Intelligence
Looks at the evolving role of humans in a machine-assisted decision loop—when to lead, when to collaborate, and when to let go. - Business Process Reengineering
Moves beyond RPA into decision intelligence: redesigning workflows to embed AI agents from the ground up. - Technology Evolution
Anticipates shifts from today’s GenAI to tomorrow’s quantum-accelerated, edge-native, or small-model ecosystems. - Governance & Compliance
Offers a practical guide to balancing regulatory agility with responsible AI practices as adoption scales.
Each of these is mapped across a maturity curve:
- Now (next 12 months)
- New (2–3 year horizon)
- Next (long-term, AI-native orgs)
It’s a rare combination of strategy and systems thinking—something most GenAI conversations gloss over.
With AI investment surging across industries—from financial services to supply chain optimization—companies are discovering a common bottleneck: organizational readiness. Pilots fail not because the models don’t work, but because people, processes, and power structures aren’t ready to adapt.
Soumendra Mohanty, Tredence’s Chief Strategy Officer, put it bluntly: “As AI agents take on more decisions, leaders must rethink when humans stay in the loop, step back, or reframe the loop entirely.”
This isn’t theoretical. Tredence drew on work with Fortune 500 clients—including Nestlé, Mars, and Casey’s—and collaborated with execs at Google Cloud, Snowflake, Forrester, and others to build the playbook. It reflects real-world pain points and hard-won lessons.
Power Tomorrow’s Intelligence — Build It with TechEdgeAI.
