Introducing the Work Different With AI Research Team

•By Vernon Keenan
Site News
Enterprise AI professionals debate overlay vs. embedded AI architecture in a modern strategy lab, with 'Work Different With AI – Choose Your Stack' displayed on a digital screen, highlighting a community-led initiative by Keenan Vision

Mapping the Next Frontier of Enterprise AI Architecture

Over the past year, I’ve argued that CIOs face their most critical architectural decision of the 2020s: embed AI deep within their systems of record or deploy an overlay of AI services above them.

Embedded AI delivers speed, security, and single-source-of-truth simplicity. Overlay AI creates a control layer offering flexibility and vendor independence. This trade-off now drives budget cycles, security postures, and board-level risk discussions.

Today, Keenan Vision launches the Work Different With AI (WDwAI) website and research team to rigorously study this critical dilemma. Our new research community, anchored at the UC Berkeley Haas School of Business, blends econometrics, field-level engineering insight, and practical go-to-market expertise.

Sponsored by Salesforce, our mandate is clear: develop decision tools—beginning with the Security Cost Function and SaaS Digital Twin Maintenance Index—that help IT leaders select and continuously optimize their mix of overlay and embedded AI.

Who’s Doing the Work

Dr. Abhishek Nagaraj joins as Principal Investigator. An Associate Professor at Berkeley Haas and a newly minted NBER Research Associate, Dr. Nagaraj brings the quantitative expertise needed to transform survey data and operational KPIs into actionable insights.

Chris Pearson joins Keenan Vision as Director of Research Programs. With 15+ years of hands-on Salesforce engineering leadership, most recently directing a 2,000-user multi-cloud deployment at Jostens, Chris integrates generative AI across every stage of the software development lifecycle, providing a critical practitioner’s perspective.

Two former Nagaraj students and recent Haas MBA graduates join as Research Fellows:

  • Stanley Choi brings experience from Capgemini Invent (management consulting) and Procore Technologies (GTM Strategy), where he guided executives through strategic initiatives and large-scale transformations. He excels at translating high-level insights into actionable strategies—bridging the gap between research and real-world adoption.
  • Alecia Wall rounds out the core team, bringing extensive channel strategy experience from Atlassian and Apple. Her perspective ensures our recommendations resonate not just with global systems integrators but also the fast-growing Managed Service Providers (MSPs) serving mid-market enterprises.

What We’ll Analyze

The overlay-vs-embedded decision impacts every dimension of enterprise AI deployment. Our research examines six critical pillars:

Enterprise AI Decision Pillars chart by Keenan Vision displaying six core areas: Risk, Compliance & Governance; Data Architecture & Integration; Delivery Velocity & Innovation Culture; Scalability & Provisioning; Cost & Run-Ops; and User Experience & Adoption, each represented with an icon in a navy blue grid layout.

Each pillar presents distinct trade-offs. Risk & Governance favors embedded AI’s unified security model, while Delivery Velocity often accelerates with overlay flexibility. Data Architecture determines whether you centralize intelligence or federate it. Cost & Run-Ops shift dramatically between consumption-based overlay pricing and bundled embedded licensing. Scalability constraints differ when provisioning dedicated AI infrastructure versus leveraging existing SaaS capacity. User Adoption depends on whether AI feels native to familiar workflows or requires new interfaces.

Our Security Cost Function quantifies these trade-offs, transforming architectural philosophy into measurable business impact.

What We’ll Produce

Over the summer, our team will:

  • Interview a diverse cross-section of IT decision-makers, security architects, and line-of-business leaders who currently manage hybrid AI environments.
  • Quantify the incremental risks and operational friction introduced—or mitigated—by overlay vs. embedded deployments, using our Security Cost Function prototype.
  • Publish a working paper in early September, accompanied by an evaluator tool that CIOs can apply directly to their own organizational data.

Why It Matters Now—and How You Can Engage

Regulators are mobilizing. Budgets are contracting. C-suites demand results beyond slideware.

By grounding the overlay-vs-embedded debate in concrete metrics we aim to equip decision-makers with a scientifically robust vocabulary that accelerates responsible AI deployments and prevents today’s quiet erosion of talent from becoming tomorrow’s skills recession.

All interim findings, field notes, and prototype tools will be shared on WorkDifferentWithAI.com—our hub for forging the Nexus of Abundance. Here, we explore the full spectrum of AI-related workplace concerns: from thriving alongside Virtual Employees, confronting the Quiet Erosion of junior roles, to understanding how the New Intelligence Gradient reshapes labor economics.We’re also launching an exclusive community where researchers and practitioners can exchange insights, critique models, and test early iterations of tools like our Security Cost Function evaluator. Join us at WorkDifferentWithAI.com/join. Whether you’re ready to share implementation experiences, beta-test our dashboards, or simply lurk and learn, your participation is vital to making the Nexus of Abundance a tangible reality.