Clients & Mandates

Who I help

I work with a specific set of leaders facing a specific set of problems, where AI complexity, governance requirements, and business stakes are highest. If that sounds like you, we should talk.

Segment 01

PE Firms & Portfolio Companies

You've completed a deal, or you're preparing for one, and AI is somewhere in the thesis. Either the diligence flagged gaps, the portfolio company has pilots going nowhere, or the value creation plan depends on operational leverage that hasn't materialized. You need someone who can assess, prioritize, and execute, not produce a study.

  • Diligence findings flag AI immaturity or data infrastructure risk
  • Portfolio company AI initiatives are fragmented with no clear ROI path
  • The investment thesis includes AI-enabled margin expansion that's not being captured
  • You need a credible AI operating narrative for the exit story
  • Your operating team doesn't have the bandwidth or AI depth to drive this internally
Buy-side & sell-side AI due diligence, use-case prioritization, and AI → EBITDA modeling at West Monroe Partners across healthcare, financial services, professional services, and industrial portfolios.
Representative engagements
  • West Monroe Partners
  • Accelerate Partners
  • Context Summits
  • Forsyth Barnes
  • + additional portfolio work available on request
What I deliver
  • AI readiness & maturity assessment
  • Use-case prioritization by EBITDA impact
  • Operating model & governance design
  • AI → EBITDA bridge for the deal narrative
  • 100-day AI execution roadmap
Segment 02

Professional Services Firms

Accounting, legal, consulting, IT services, and cybersecurity firms, many of them PE-backed and growing through acquisition. The economics are unforgiving: revenue walks out the door every evening, margin lives in utilization, billing, and cash conversion, and every acquired firm arrives with its own systems, data, and habits. AI changes how expert work gets done, but only if the firm has the data foundation, governance, and operating model to put it into daily practice.

  • Growth by acquisition has left a patchwork of practice management, billing, and CRM systems
  • Billing, invoicing, and collections cycles leak margin and stretch cash conversion
  • Partners and practice leaders lack a trusted, firm-wide view of client and engagement economics
  • AI tools are being adopted practice by practice, with no common governance for client confidentiality
  • The value creation plan assumes operating leverage that technology has not yet delivered
Led data and AI diligence for a multi-office accounting, tax, and advisory firm ($500M to $1B revenue): service-line disruption risk, use-case and build vs. buy priorities, and a phased roadmap targeting 10 to 20% efficiency gains within a year. Technology, data, and AI diligence at West Monroe on transactions involving consulting, IT services, law, cybersecurity, and software firms. As CIO and CDO of Radiant Healthcare, a revenue cycle, credentialing, and analytics services firm, scaled technology through sevenfold growth with 30%+ cost savings. As interim CDAO of a national physician services organization, lifted billing productivity 15%, cut invoice processing time 40%, and reduced DSO by 10 days.
Firm types I have worked with
  • Accounting, tax, and advisory firms
  • Multi-service-line consulting firms
  • IT services and consulting firms
  • Law firms
  • Cybersecurity firms
  • Software product companies
  • Healthcare business services firms
What I deliver
  • Technology, data, and AI diligence
  • Post-acquisition systems and data integration roadmap
  • Billing to cash and engagement economics analytics
  • AI for document and knowledge work, with human review
  • AI governance built for client confidentiality
Segment 03

Regulated Enterprises

Healthcare payers, providers, and financial services organizations operating under strict compliance requirements, legacy data infrastructure, and board-level AI scrutiny. You have real AI ambitions but real constraints, regulatory risk, model governance requirements, fragmented data, and leadership teams that don't yet agree on what AI should actually do.

  • AI pilots are running but not scaling, or scaling without governance
  • The board or regulators are asking questions about AI risk and oversight
  • Data infrastructure is fragmented across legacy systems and cloud platforms
  • You've hired AI talent but don't have the operating model to deploy them effectively
  • AI spend is growing but ROI accountability is weak or nonexistent
$53M transformation, $10M+ savings in 12 months as CDO + Chief AI Officer at CareFirst BlueCross BlueShield; 30%+ cost savings at Radiant Healthcare; RCM and billing productivity at Envision Healthcare.
Representative clients
  • CareFirst BlueCross BlueShield
  • Radiant Healthcare
  • Envision Healthcare
  • ZS Associates
  • AMN Healthcare
  • Thomas Jefferson University
  • Pfizer
  • Vanguard
  • iConnections
  • Capgemini
  • + additional Blues & health plans
  • + additional FS engagements
Segment 04

Boards & C-Suite

You're a CEO, CFO, or board member navigating AI strategy with an information asymmetry problem. Your technology team is telling you AI is progressing. Your instincts say something's off, the metrics aren't clear, the governance isn't real, or the strategy hasn't been tested against the business model. You need an independent perspective from someone who has sat in the chair.

  • You want an independent AI audit not produced by the people running AI
  • The board needs AI literacy, not hype, not fear, but operational clarity
  • You're evaluating a CTO, CDO, or CAIO hire and want a credible reference point
  • An acquisition target's AI claims need pressure-testing before close
Board of Advisors at A3.AI (nonprofit AI applied R&D); Board of Directors at Humanim. Executive briefings, AI governance reviews, and C-suite advisory engagements.
Advisory formats
  • Quarterly board AI briefings
  • Independent AI strategy audit
  • Executive AI literacy workshop
  • CAIO / CDO hire evaluation support
  • Acquisition AI due diligence
Typical commitment

One to two days per month. Project-based engagements also available for discrete reviews and diligence work. Scope and structure discussed on discovery call.

Client Experience

Representative organizations

A cross-section of organizations I've worked with directly or through Soft Solutions Partners. Names used where disclosed. Additional references available in conversation.

Vanguard
Envision Healthcare
Radiant Healthcare
Capgemini
iConnections
Pfizer
AMN Healthcare
ZS Associates
Thomas Jefferson University
Oliver James
Accelerate Partners
Forsyth Barnes
Context Summits
APWireless
PEG Bandwidth
+ more
Honest disclaimer

This isn't for everyone

Being direct about fit saves everyone's time. Here's where I'm genuinely not the right match.

Early-stage startups without data infrastructure
My expertise is in scaling AI in complex environments with existing data assets, compliance requirements, and operational workflows. If you're pre-product or pre-data, the engagement won't deliver what you need.
Pure product-engineering AI roles
I'm an enterprise operator, not a product builder. If the mandate is to ship AI features into a consumer product, there are better-suited people. My edge is business value, governance, and operating model, not product roadmaps.
Organizations not ready to act on findings
I don't do advisory theater. If the goal is to have a credible-sounding AI strategy for internal optics, without the commitment to act on what we find, we'll both be disappointed.
Generic AI consulting without business accountability
Engagements where success is defined by deliverables rather than outcomes aren't where I do my best work. I prefer mandates where we can agree upfront on what measurable improvement looks like.
Sound like your situation?

Let's find out if
there's a fit.

30 minutes. No pitch deck. A direct conversation about what you're working on.

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