About
Independent AI value creation for enterprise executives
J.L. Sutherland & Associates was founded to address a gap in the market: enterprise leaders need trusted, independent guidance on AI transformation— not vendor pitches disguised as consulting.
Joe Sutherland, PhD
President & CEO
With a career spanning the Dow Jones 30, The White House, and our nation's top universities, Joe Sutherland has attracted clients such as Canva, Goldman Sachs, GlaxoSmithKline, Cisco, Coca-Cola, The Conference Board, and Fulcrum Equity Partners. After deploying his first software written in BASIC in 1998, his career spanned executive roles at Cisco and Amazon, co-founding acquired FinTech and AI startups, and building AI programs at a major research university and academic health system.
His work has been widely published in popular and academic presses. His book, Analytics the Right Way: A Business Leader’s Guide to Putting Data to Productive Use (Wiley), was an international bestseller within 30 days of its release. His annual schedule regularly includes delivering 8-10 keynotes on the topics of enterprise AI, innovation, and the societal implications of AI.
Joe earned his PhD, MPhil, and MA from Columbia University, and his BA from Washington University in St. Louis.
Credentials
Operating Experience
- Executive at Cisco and Amazon leading data, analytics, and AI transformation
- Executive at Emory University and Emory Healthcare building enterprise AI capabilities and the workforce of the future
- Co-founder of a FinTech startup acquired after 8-figure exit
Thought Leadership
- Speaker at industry conferences on AI strategy and governance
- Faculty teaching AI and analytics to MBA, executive, and PhD audiences
Platform Fluency
Deep familiarity across major platforms—vendor-agnostic but technically grounded:
Analytics the Right Way
Analytics the Right Way is a boardroom-friendly guide to using data productively and profitably—built for leaders who are tired of dashboards that don't drive decisions and AI pilots that don't scale. The same operating disciplines that make analytics work—measurement, governance, economics, and enablement—are what make AI durable.
- A clear mental model for decisions under uncertainty (so teams stop talking past each other).
- Three value-producing uses of data: performance measurement, hypothesis validation, and operational enablement.
- How to avoid common failure modes: 'data thrown at me,' unclear ROI, and reporting that can't be trusted.
- How to scale responsibly: auditability, controls, and pragmatic governance.
- How to build capability so the organization can run without permanent dependency.
University anchor & public service
Beyond client work, Joe maintains deep ties to academic and public institutions— teaching, building programs, and contributing to workforce development initiatives.
- Executive at Emory's Center for AI Learning, building enterprise AI capabilities and the workforce of the future across a university and health system
- Faculty teaching AI strategy, governance, and analytics to MBA, executive, and PhD audiences
- Statewide leader of public–private AI upskilling initiatives designed to reach 10,000+ participants
- Principal Investigator at the US Center for AI Standards and Innovation
- AI Commission Member for the City of Atlanta
- Regular media contributor on AI developments and enterprise adoption
How we work
Principles that guide every engagement and differentiate our approach from traditional consulting models.
Independent perspective
No vendor partnerships, no referral fees, no platform agendas. Our recommendations are based solely on what's right for your organization.
Outcome alignment
We structure engagements around measurable results, not billable hours. Our success is tied to your success.
Executive-grade communication
Board-ready deliverables, concise recommendations, and direct access to senior practitioners throughout every engagement.
Knowledge transfer priority
Every engagement includes structured capability building so your team can sustain momentum independently.
Platform-fluent. Vendor-agnostic.
We implement in the systems you already run—choosing tools based on outcomes, governance posture, and unit economics (not affiliations).
No referral fees. No reseller incentives. Recommendations are defensible and measurement-led.
Cloud & Managed AI Platforms
Managed GenAI Model Hubs
LLM Providers (Proprietary APIs)
Open-Model Hosting & Inference
Local / On-Prem LLM Runtimes
Data Warehousing & Lakehouse
Platform fluency is not platform affiliation. Tool choices follow your constraints: security, compliance, cost, and adoption.
Trusted by leaders at
Fulcrum Equity Partners
Atlanta Gas Light
Balto.ai
The Conference Board
Auburn University
Ameris Bank
Azalea Health
AAPOR
Mentor Collective
BasisTechAvoiding hype and fee gouging
The AI consulting market is rife with inflated claims and misaligned incentives. Our approach is deliberately different:
- Conservative estimates: We use ranges and contingencies, never hockey-stick projections without supporting evidence.
- Outcome-based pricing: Where appropriate, we tie compensation to measurable results, not hours logged.
- Clear scope boundaries: We define what we will and won't do upfront, preventing scope creep and surprise bills.
- Rapid off-ramps: If an engagement isn't delivering value, we help you course-correct or wind down gracefully.
- Knowledge transfer: We build your team's capabilities, not dependency on external consultants.
