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The Enterprise AI Shift

From Experiments to Orchestrated Intelligence

Early AI pilots delivered pockets of value but failed to scale. Learn what separates organizations achieving enterprise-wide AI transformation from those stuck in experimentation.
70%
enterprises adapt unified AI orchestration by 2030 (Gartner)

33%
orgs using GenAI within 1 year of ChatGPT (McKinsey)

40%
plan to increase AI investment (McKinsey)

5% vs 70%
unified platforms today vs 2030 (Gartner)

  • Identify why early AI pilots failed to deliver organization-wide transformation
  • Build governance frameworks that enable confident AI deployment
  • Navigate the shift from isolated AI tools to unified orchestration
  • Prepare for AI agents with clear policies and escalation paths
  • Apply five expert predictions to your 2026-2030 AI strategy

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This ebooks features research from McKinsey & Company and Gartner

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What's Inside

First Wave Lessons

First Wave Lessons

What organizations learned from early AI deployments – and why models alone weren’t enough.

  • AI in isolation produced inconsistent results
  • Model performance tied to data quality
  • Non-deterministic outputs unacceptable for regulated decisions

The Orchestration Imperative

The Orchestration Imperative

Why enterprises are shifting from fragmented pilots to unified BOAT platforms.

  • Separate pilots led to overlapping tools
  • Real value when AI embedded in end-to-end processes
  • Rules engines provide deterministic backbone

Five Predictions: 2026-2030

Five Predictions: 2026-2030

Expert forecasts on how enterprise AI will evolve.

  • AI ROI depends more on orchestration than model selection
  • AI agents will become standard
  • Agentic workflows replace static automation

Who This Guide Is For

CIOs &
CTOs

Setting enterprise AI strategy, standardizing on platforms, ensuring AI delivers value without risk.

IT & Enterprise Architects

Designing technical foundation for AI – connecting models, agents, workflows, and rules.

Heads of Operations

Embedding AI into core processes, defining where automation acts vs. where humans intervene.

Compliance Leaders

Ensuring AI decisions are repeatable, auditable, and aligned with regulatory requirements.

“By 2030, 70% of enterprises will adopt unified platforms that orchestrate business processes, AI agents, bots, APIs and human actions – up from just 5% today.”
Gartner

The Enterprise AI Shift eBook screenshot

Ready to move from AI experiments to enterprise transformation?

Get the complete framework for governed, orchestrated “AI – plus five predictions to guide your 2026-2030 strategy.

Read the Enterprise AI Shift

Ready to move from AI experiments to enterprise transformation

FAQs

Lessons from first wave GenAI adoption, shift toward governance and orchestration, core priorities for AI maturity today, and five expert predictions for 2026-2030.

CIOs, CTOs, IT architects, heads of operations, and governance leaders responsible for AI at enterprise scale. Especially relevant for regulated industries.

Early pilots failed to scale because they ran in isolation. AI orchestration connects models, agents, and automation into a unified platform for consistent results.

Business Orchestration and Automation Technologies – Gartner’s term for platform unifying process design, rule management, workflow automation, and AI orchestration.

The guide includes ‘What This Means for Technology Leaders’ section with specific imperatives for standardizing on orchestration.

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