AI Strategy 2025: Executive Priorities from J.P. Morgan’s Emerging Technology Trends

Sep 25, 20254 min read

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Executive Summary

The 2025 Emerging Technology Trends report from J.P. Morgan makes one point clear: artificial intelligence is no longer a side experiment — it is the operating system of business. Executives face a shifting environment where innovation, regulation, and infrastructure collide. From AI’s new “scaling laws” to geopolitical re-architecting of data centers, the next two years will determine which firms lead and which fall behind.

This article distills the report into executive-level priorities:

Innovation strategy: Navigating scaling laws, synthetic data, and automation convergence.
Geopolitical shifts: Data sovereignty, energy security, and the BYOC model.
Infrastructure bottlenecks: Compute demand, power constraints, and next-gen data center design.
Actionable risks: Guardrails, governance, and trust in an AI-first economy.

Innovation Strategy: Beyond GenAI Hype

Generative AI has already transformed content creation, marketing, and customer interaction. What’s emerging in 2025 is a strategic shift from training to reasoning.

Scaling Laws, Reimagined: The industry is moving beyond the brute force of pre-training massive models. Innovation now hinges on inference-time compute and reasoning models. This is the AI equivalent of Moore’s Law for the next decade. For C-suites, it signals where to direct R&D spend: compute capacity and post-training innovation rather than only data acquisition.
Synthetic Data as IP: By 2025, 60% of AI training data will be synthetic. But the real breakthrough is its use in post-training, where models generate and evaluate their own “chains of thought.” This accelerates reasoning capabilities and creates proprietary intellectual property. For boards, the question becomes: who owns the governance and competitive advantage in synthetic pipelines?
Automation Convergence (BOAT): Traditional RPA and GenAI are merging into unified Business Orchestration and Automation Technologies. This represents not just efficiency gains but platform consolidation. Vendor strategies must evolve — piecemeal automation tools will be displaced by orchestrated ecosystems.
Maturity Roadmaps (RAG to Agentic Systems): Retrieval-Augmented Generation (RAG) is evolving from simple vector search to Hybrid RAG (knowledge graphs) and ultimately to Agent-powered RAG. For CIOs, this maturity model provides a benchmark to evaluate current deployments and plan staged adoption.

Geopolitical Shifts: Energy, Sovereignty, and Control

AI strategy is no longer confined to algorithms. It is deeply geopolitical.

Data Sovereignty and BYOC: The report highlights the rise of Bring Your Own Cloud (BYOC) as a middle ground between SaaS and self-hosting. This model balances control, compliance, and scalability. For industries under regulatory pressure — finance, healthcare, public sector — BYOC is fast becoming a boardroom conversation. In parallel, Bring Your Own Model (BYOM) offers flexibility for enterprises wary of vendor lock-in.
Infrastructure and Energy Security: AI’s hunger for compute is colliding with power constraints. Hyperscalers are already making long-term bets, co-locating data centers near alternative energy sources, including nuclear. These moves are not just about cost — they reshape global supply chains and influence national energy policy. Executives must view data center strategy as both a technology and geopolitical decision.
Regional Divergence: North America remains the adoption leader, Europe is pursuing a regulation-first path, and APAC is accelerating deployment in retail and mobility. For multinational executives, strategy must flex: compliance rigor in Europe, innovation pilots in APAC, and scaling efficiency in North America.

Infrastructure Bottlenecks: The New Limits to Growth

Every transformation has constraints. For AI, they are increasingly physical.

Compute Economics: Inference-time compute is the new cost driver. Budgets must shift from one-off training events to ongoing reasoning cycles. CFOs and CTOs must jointly oversee how compute costs are integrated into long-term operating budgets.
Next-Gen Data Center Design: Sustainability is no longer a branding exercise — it is a requirement. Meeting ESG goals while running AI workloads means re-architecting facilities, sourcing renewable and nuclear energy, and designing for efficiency at scale. Hyperscalers are setting the benchmark; others must follow or risk obsolescence.
Edge and On-Device AI: The $114B market forecast for on-device AI highlights an alternative path. Processing closer to the user improves privacy, speed, and efficiency. For industries constrained by compliance, on-device intelligence is not optional; it is a strategic hedge.

Actionable Risks: Guardrails for an AI-First Enterprise

The report’s Risk Radar underscores that AI’s upside is matched by systemic vulnerabilities.

AI Overreach: Projects without clear ROI create shallow wins and long-term tech debt. Boards should demand disciplined project selection.
Synthetic Data Misuse: Governance gaps can amplify bias or generate reputational fallout. Establishing a synthetic data governance board is a near-term priority.
Agentic Security Gaps: Multi-agent systems risk unauthorized transactions or data exposure without guardrails. CISOs must adopt “agentic security” frameworks before scaling deployment.
Energy and Sustainability Strains: Power consumption is now a board-level issue. Firms must balance AI expansion with sustainability targets.
Deepfake Manipulation: Fraud and misinformation pose trust risks to both consumer and enterprise ecosystems. Building counter-AI defenses is no longer optional.

Executive Priorities: The 2025 Checklist

For leaders seeking to future-proof strategy, the report translates into an actionable agenda:

Reallocate SEO/SEM budgets toward Generative Engine Optimization (GEO).
Establish governance boards for synthetic data pipelines.
Fund pilots for confidential AI enclaves in sensitive workflows.
Adopt multi-agent orchestration frameworks with built-in security.
Incorporate compute and energy costs into multi-year budgets.
Evaluate BYOC/BYOM hosting models for sovereignty and flexibility.
Benchmark automation platforms against the BOAT convergence trend.
Prioritize AI-driven employee experience tools to enhance productivity and retention.
Engage CISOs early in adopting agentic cybersecurity operations.
Track hyperscaler moves in energy and infrastructure as macro-level signals.

Conclusion: Competing in the Age of Strategic AI

J.P. Morgan’s 2025 Emerging Tech Trends report makes the stakes clear: AI is shifting from experimentation to infrastructure, from technical problem to strategic imperative. For C-suites, the challenge is no longer whether to adopt AI, but how to align it with corporate strategy, geopolitical realities, and long-term resilience.

The winners of 2025 and beyond will not be those who adopt AI fastest, but those who adopt it wisely — balancing innovation with governance, growth with sustainability, and scale with trust.