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Robert Vaughn Elliott

Strategy · Agentic AI · Design Science · Data Science

Strategy for complex problems in an agentic AI era.

I research how agentic AI can support strategy design—combining abductive reasoning, proven strategy design processes, and data science with decades of experience turning complex problems into business outcomes.

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About

The work has changed. The problem has not.

Much of my career has been spent where technology, economics, organizations, and difficult decisions intersect.

At ISM, IBM, Intria-HP, and TELUS, that meant helping shape managed-services capabilities, outsourcing arrangements, large complex deals, strategy, innovation, and roadmaps. The technologies changed. The recurring challenge was translating complexity into something an organization could understand, decide on, and execute.

Today, I am bringing that practitioner experience into a new research question:

How can agentic AI support the way organizations design strategy?

My work explores that question through agentic artificial intelligence, abductive reasoning, and data science, and proven strategy design processes— particularly where solutions to problems are ambiguous, interconnected, and resistant to a single “right” answer.

My 2025 paper starts with a very human obstacle: the cognitive biases that quietly narrow the options a group is willing to consider—and how artificial intelligence might widen them.

The goal is not AI for its own sake. It is better ways to frame problems, explore alternatives, make decisions, and turn strategy into action.

Current research

Can generative AI help strategy workshops think more broadly?

My original research asks whether generative artificial intelligence, guided by carefully structured prompts, can produce useful insights and genuinely new strategic ideas inside the University of Cambridge’s strategic roadmapping workshop process, known as S-Plan.

Working paper · SSRN · 2025

Using Generative AI to Mitigate Cognitive Biases in Strategic Roadmapping Workshops

R. Vaughn Elliott

Strategy workshops rely on diverse participants to counter the blind spots we all carry. This paper shows how generative artificial intelligence can add another kind of diversity— generating insights and a short list of strategic hypotheses that people then review, discard, refine, or combine with their own.

Read the abstract

Cognitive biases in humans are primarily involuntary phenomena that require active mitigation in innovation processes, including strategic roadmapping. Cambridge’s strategic roadmapping process (S-Plan) includes features to mitigate cognitive biases of workshop participants, but these analogue techniques are imperfect. The aim of this article is to demonstrate how generative artificial intelligence (GAI) can be used to further mitigate cognitive biases in S-Plan workshops.

A key analogue technique is to involve a diverse group of participants, mitigating biases through cognitive diversity. This paper establishes that GAI, used within an abductive reasoning process, can further increase cognitive diversity. During the early ideation phases, GAI generates insights and a short list of strategic initiative hypotheses to be reviewed, discarded, revised and/or combined by workshop participants with their own ideas for future testing.

Read paper on SSRN ↗

What the research does

  • The problem: biases that narrow strategy

    Cognitive biases—favouring the status quo, seeking confirming evidence—quietly limit which futures an organization will consider. It is the pattern behind the "Innovator's Dilemma," where successful firms see change coming and still fail to act. Diverse workshops help, but they are imperfect.

  • The approach: design science, with humans in control

    Using design science research approach, I built a Python-based, AI-augmented version of the S-Plan process. Multiple personas work step by step through strengths, weaknesses, opportunities and threats (SWOT) and its strategy-matching counterpart (TOWS). People stay in charge throughout ("AI-in-the-loop"), and ethics are designed into the approach from the start.

  • What it found: broader, traceable ideas at low cost

    A simulation in the Canadian telecommunications industry showed the persona-based prompt series produced higher-quality and more unusual ideas than simple prompts, each backed by traceable insights—for roughly one Canadian dollar per run.

Where it goes next: comparing newer models, field testing with real workshops and practitioners, carrying ideas forward into roadmap development, and exploring how agentic artificial intelligence could support the development and testing of strategic abductive hypotheses.

Foundations

Experience that shaped the work

Most of my career has been spent helping shape new customer solution strategies—and helping sales teams close the large opportunities those solutions made possible.

  • IBM / ISM / SaskCOMP · 1984–1999

    Building managed-services capability

    Part of the teams that developed IBM Global Services Canada's data-centre and desktop outsourcing capabilities and offerings, including the IBM/Bell strategic alliance—an agreement of roughly a billion dollars signed in 1996.

  • Intria-HP · 1999–2002

    Turning infrastructure into a services model

    Led and supported segments of the work that transformed a CIBC (Canadian Imperial Bank of Commerce) technology cost centre into a multi-billion-dollar outsourcing agreement and the foundation for HP Enterpise Services in 2002.

  • TELUS · 2002–2020

    From complex deals to strategy and innovation

    Led and took part in several large, complex deals with billions of dollars of combined total contract value, as well as supporting strategy, innovation, and product market development for TELUS Business (Enterprise).

Recognition: twice named to the President’s Club at TELUS, with equivalent awards at ISM (later IBM Global Services Canada) and Intria-HP (later HP Enterprise Services).

Education

A career built on learning across disciplines

My formal education has followed the same questions as my work—from computing, to the economics of decisions, to data and artificial intelligence.

  • Bachelor of Science, Computer Science — Distinction

    University of Regina

    1984

  • Master of Science, Financial Management

    University of London

    2000

  • Master of Science, Data Science & Artificial Intelligence — Distinction

    University of London / Goldsmiths · research project developed into the working paper above

    2025

Capabilities

What I bring to the problem

  • Strategy & innovation
  • Strategic roadmapping
  • Design science research
  • Abductive reasoning
  • Data science
  • Artificial intelligence & agentic AI
  • Systems thinking
  • Facilitating strategy workshops
  • Large complex deals
  • Managed-services development
  • Solution development
  • Financial management
  • Information & communications technology

Current focus

What I’m researching now

  • Agentic artificial intelligence
  • AI-augmented strategy design
  • Cognitive bias in strategy
  • Strategic roadmapping
  • Design science research
  • Data science

Contact

Interested in the same questions?

I am interested in conversations at the intersection of strategy, agentic AI, design science, data, and complex organizational problems—particularly where emerging technology has to become something practical.

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