Strategy. Implementation.
Value Creation.
We help Boards and CEOs move AI from experimentation to measurable enterprise value — with clear strategy, practical governance, and implementation leadership grounded in two critical questions: Is our data ready for AI, and are our IP and sensitive information protected? For growth-stage and mid-market companies — from pre-revenue biopharma to established enterprises — across life sciences, healthcare, and other data-driven sectors.
We advise growth-stage and mid-market companies where AI, data, technology, and governance decisions have turned strategic.
Often the difference isn't ambition — it's that leadership doesn't yet have the internal capacity, operating model, or executive technology experience to move with confidence. That's the gap we fill. We're particularly well suited for:
Seeking a clear AI agenda, risk view, and governance model.
Moving from AI interest or experimentation to practical business value.
Focused on value creation, productivity, and scalable operating discipline.
Preparing for scale, commercialization, data maturity, or investor scrutiny.
That don't yet have a CIO, CDO, CAIO, or mature IT/data function.
Life sciences, pharma services, healthcare services, diagnostics, technology-enabled services, and other data-driven businesses.
The AI bottleneck isn't the technology. It's embedding it inside your business workflows — strategically, operationally, and profitably.
Strategy + Execution = Success.
Most consultancies leave after the roadmap. We stay, build, and ship. The engagement isn't done until something works in production.
Value Creation is the goal.
Shipping AI isn't the goal — moving the P&L is. Every engagement ties to value pools, ROI, and adoption you can measure and defend to the board.
Governance protects the value.
Gains that can't be governed don't last — and the fastest way to lose them is a security or data breach. We build the guardrails, cybersecurity discipline, and oversight that guard against data and IP leakage, so the business can move at speed with the board's confidence.
Sound familiar?
If you're a Board member or CEO, you've heard at least three of these in the last quarter. Most share one root cause: a gap between AI ambition and the operational reality of turning it into value.
No coherent answer, no roadmap, and the competitive landscape is moving. The CEO needs a strategy that's specific to the business — not a generic deck.
The slides look great. Nothing's in production. Vendors are circling. The team is exhausted and the CFO is asking pointed questions about ROI.
A customer, regulator, or insurer wants documentation. The legal team is improvising. Use is already widespread inside the company — without rules.
Each promises transformation; each has a different price tag and procurement path. You need an independent voice in the room — not another sales pitch.
PE deal or strategic acquisition. The target claims an AI moat. You have two weeks to assess what's real, what's marketing, and what becomes a Day-1 liability.
Strong leaders, but no one has lived through an AI transformation. Hiring an in-house AI exec is a year-long search. You need someone embedded — now.
Three pillars. One firm.
Most engagements span at least two of the three. The advantage of one firm carrying strategy through implementation through value creation is that nothing gets lost in handoff — the people who set the agenda are the people who build the systems and prove the value.
Strategy
Where AI belongs in your business — and where it doesn't.
A working AI strategy is not a list of use cases. It's an honest map of where AI will create durable value in your business, where it won't, and what to do first. Board-ready, CFO-defensible, and rooted in what your business actually looks like — not a vendor's slide template.
- AI Opportunity AssessmentWorkflow-by-workflow scan of where AI creates leverage, where it creates risk, and where it's a distraction. Scored by impact, feasibility, and time-to-value.
- Executive & Board AdvisoryBriefings, board memos, and quarterly check-ins. A fluent partner in the room when the question is "what about AI?"
- AI Roadmap & Investment Plan12 to 36 months, sequenced. What to build, what to buy, what to wait on. Includes capital plan and capability-build trajectory.
- Vendor & Tool SelectionIndependent diligence on Copilot, Claude, Glean, Writer, Cohere, custom build, and the integrators pitching you. We don't take referral fees.
- M&A & Investment DiligenceFor PE firms, family offices, and corp-dev teams: rapid assessment of an AI claim in a deal. What's real, what's marketing, what's a post-close liability.
A signed strategy document the CEO, CFO, and board agree on. Specific enough to act on Monday; durable enough to live for three years.
Implementation
Working systems in production. Not slides. Not pilots that die.
Implementation is where most AI work dies. The handoff from strategy to engineering goes wrong; the team doesn't know how to operate LLM systems; the vendor's reference architecture doesn't fit your stack. We embed alongside your team, ship working systems, and transfer capability as we go.
- Production AI AgentsInternal agents for sales ops, finance close, customer ops, knowledge retrieval, document workflows. Built on your data, in your environment.
- System Integration & Data PipelinesConnecting LLMs to your CRM, ERP, ticketing, document stores, and warehouses. With retrieval that actually works on your messy data.
- Workflow AutomationTargeted automation of high-leverage workflows — RFP responses, contract review, invoice processing, customer onboarding, executive reporting.
- Embedded Build TeamsSenior engineers and PMs working alongside your team for 8 to 26 weeks. We sit in your standups, ship in your repos, and leave behind operators who can run the system.
- Capability Transfer & TrainingHands-on training for your internal team so the work outlives the engagement. We don't build dependency; we build operators.
A working system in production, with monitoring, fallback paths, and a team inside your company that knows how to operate it.
Value Creation
Turning AI from cost and experimentation into measurable enterprise value — governed so it lasts.
Value Creation is where the work pays off. We size the opportunity, build the value cases, track ROI and adoption, and put the governance and risk discipline in place so the gains are real, durable, and defensible to the board. Aligned to NIST AI RMF and ISO/IEC 42001 where it matters; readable by humans where it doesn't.
- Opportunity Sizing & Value CasesWhere AI moves the P&L — growth, productivity, cost, and risk. Quantified value pools and business cases the CFO will defend.
- ROI & Adoption TrackingBaselines, value measures, and adoption metrics so benefits are realized — not just promised. Reported on a cadence the board can read.
- Governance, Security & Risk FrameworkPragmatic policy, controls, and human-in-the-loop design — with cybersecurity and data protection built in. Aligned to NIST AI RMF and ISO/IEC 42001 where useful; PHI/PII-aware for regulated work.
- Operating Model & OversightWho owns AI, how decisions get made, and how the board oversees strategy, risk, and value over time.
- Benefits RealizationClosing the loop from roadmap to results — so the value committed in the strategy actually shows up in the business.
A value scorecard and governance package: quantified benefits, adoption metrics, risk controls, and a board reporting cadence — proof the AI investment is paying off.
Why companies hire us.
Boards and CEOs don't need another deck — they need AI that moves the business. Pickett Strategy Group pairs board-level strategy with hands-on execution, so the agenda becomes measurable enterprise value.
- Board-ready AI strategy and risk narrative
- Prioritized use-case portfolio with investment requirements tied to business value
- Practical governance and operating model
- 90-day roadmap with owners, milestones, and value measures
- Recommended AI tools and technology stack
- Where can AI create measurable value now?
- Is our data ready, governed, and good enough for AI?
- Is our AI secure — what is our cybersecurity and risk exposure?
- Which opportunities should we fund, scale, or stop?
- What AI technology should we use — and should we buy, build, or partner for implementation?
- How do we measure ROI, adoption, productivity, and risk reduction?
Three phases. One engagement.
Every engagement follows the same arc, scaled up or down by scope. Discover first — fast — because most of the cost of bad AI work is doing the wrong work well. Then build. Then prove and govern the value, with the board kept in view.
Discover
Interviews with the executive team, workflow mapping, a data-readiness and system audit, a cybersecurity & AI risk review, opportunity scoring, and a board-ready strategy document. Output is a roadmap you can defend to the CFO — and the board's two first questions, data and security, answered up front.
- // Executive interviews (CEO, CFO, COO, CTO, functional leads)
- // Data readiness, quality & access assessment
- // Cybersecurity & AI risk posture review
- // Vendor & tech landscape mapping
- // Opportunity scoring (impact × feasibility × time-to-value)
- // Governance & risk baseline
- // Board-ready strategy & roadmap document
Deploy
Build the first two or three production systems. Embedded engineers, your data, your environment. Integrations, monitoring, fallback paths, and the human-in-the-loop controls designed in from day one.
- // Solution architecture & vendor selection
- // Production build (agents, retrieval, integrations)
- // Connection to your CRM / ERP / document systems
- // Acceptable-use policy & risk controls in place
- // User training & rollout to first cohort
- // Capability transfer to your internal team
Govern & Operate
After Deploy, most clients keep us on a fractional basis — quarterly governance reports, expansion to new workflows, ongoing executive advisory, and a phone number to call when something changes in the landscape.
- // Quarterly governance review & board reporting
- // Model & vendor monitoring
- // Expansion to next-priority workflows
- // Ongoing executive & board advisory
- // Crisis response & incident review
- // Strategic refresh every 12 – 18 months
Straight talk.
Six things that separate Pickett Strategy Group from the consultancies and the resellers.
Strategy and execution from the same people.
The senior person who wrote your roadmap is the senior person on the build. Nothing gets lost in translation because there's no translation.
We don't take referral commissions.
Vendor recommendations are based on fit, not kickbacks. If you ask us "Copilot or Claude?", you get an answer based on your stack — not our P&L.
The people in the room are the firm.
No farming out the build to a partner network. The team you meet in week one is the team in week sixteen.
If we don't know, we say so.
AI moves fast. Some questions don't have answers yet. We'll tell you what's known, what's contested, and what's marketing.
We measure ourselves in tangible business value created.
Not slide counts or hours billed. Strategy reads like writing, implementation is working software, and success shows up as measurable value in the business.
We build to leave behind.
Capability transfer is a deliverable, not a marketing line. Most clients keep us on a small fractional basis after; none are forced to.
Founder & principal.
Pickett Strategy Group is founder-led by Larry Pickett. Every engagement runs through him; the team scales around him, not in front of him.
Three decades pairing board-level strategy with hands-on transformation.
Larry founded Pickett Strategy Group to do one thing well: help Boards, CEOs, and PE-backed companies turn AI from a board topic into measurable enterprise value. The firm exists because the gap between AI strategy and AI execution is where most value is lost — and where most consultancies stop.
The work is rooted in a simple operating belief: strategy without execution is theater, execution without value is activity, and value without governance is fragile. A useful advisor carries all three. Pickett Strategy Group is built around that proposition.
Engagements span the U.S. and serve Boards, CEOs, PE firms, and portfolio companies across life sciences, healthcare, and other data-driven sectors — from pre-revenue and growth-stage companies to established mid-market enterprises. Before founding the firm, Larry served as a Chief Information & Digital Officer and multi-time CIO, and was co-founder and former CEO of a Data Science / AI company serving pharmaceutical clients — a successful exit with strong investor returns.
Common questions.
The questions that come up on the first call, answered plainly. If yours isn't here, ask it — the email and phone are at the bottom.
Let's talk.
Tell us where you are. A 30-minute executive call will tell you whether an AI Strategy & Readiness Assessment is the right next step — and if we're not the right fit, we'll usually know who is.