Where we come in
We recognize the situation you're in.
Transformation doesn't happen in the abstract. It happens when a specific leader has a specific problem and needs someone who has actually solved it before. Here's where PCG enters — and what we do when we get there.
Title varies by org size. A $20B enterprise's CIO and a $400M company's Director of IT often own the same problem. We anchor to the role, not the title.
C-Suite
CEO · COO · CIO · CTO · CFO · Chief Transformation Officer · Chief Data Officer · Chief AI Officer
What you own
The AI story to the board. The budget. The cross-functional mandate. The political capital.
You reach for us when
- —The board has asked "what's our AI strategy" and the honest answer is "we don't have one yet"
- —A competitor announced an AI initiative and you need a credible response — not a copycat
- —An earnings call or investor day is coming and the AI narrative is thin
- —A new CIO/CTO/Chief Transformation Officer is in their first 90 days and needs a defensible plan, fast
- —An inherited AI program is stalled, over-budget, or politically toxic
- —M&A integration has surfaced wildly different AI maturity on the two sides
- —A risk event — model bias, data leakage, a hallucination that reached customers — has exposed a governance gap
- —A regulator, auditor, or major customer has started asking AI questions the organization can't answer
- —The CFO has been challenged on AI ROI and the math isn't there
- —A cost-takeout mandate has landed and AI is supposed to be the lever — but nobody knows where to pull it
Where we enter
AI Readiness & Roadmap · AI Governance & Operating Model
VP
VP of Operations · Technology · Data/Analytics · Transformation · HR/People · Product · Customer Experience · Risk
What you own
Turning the C-suite mandate into something real inside your function.
You reach for us when
- —You've been told "make AI work here" and have three to five pilots running, none scaling
- —Budget is approved and the vendor is selected, but no delivery framework exists to land it
- —A cross-functional initiative is stuck because no one owns the operating model
- —You have to present an AI roadmap at the next ops review and don't want to wing it
- —You've inherited a vendor mess — overlapping tools, no clear architecture, sunk cost everywhere
- —Your team doesn't have the skills to operationalize what leadership bought
- —Middle management is quietly resisting, and the change management plan is "send another email"
Where we enter
Agentic AI-Enabled Business Process Transformation · AI Governance & Operating Model
Director · PMO · EPMO
Director of Innovation · IT · Data Science · Risk/Compliance · Process Excellence · Operations · PMO Director · EPMO Leader
What you own
Delivery. The day-to-day. The people doing the work. You often become our primary operating partner once an engagement is running.
You reach for us when
- —A specific use case has been identified and needs hands-on build-out
- —Process redesign is required to make an AI tool actually useful
- —Your team is anxious about AI's impact on their roles and needs a credible plan
- —Policy and governance documentation is required for an audit or compliance review
- —A failed pilot needs a post-mortem and a path forward
- —Program or portfolio governance needs to be rebuilt around AI-native delivery standards
Where we enter
Agentic AI-Enabled Business Process Transformation · AI Readiness & Roadmap
Hear something familiar? Here's where it leads.
Nine industries with the highest AI regulatory pressure. Not a generic checklist.
Financial Services
Model risk management (SR 11-7 lineage) and third-party AI accountability are the questions every regulator is asking. OCC, Fed, and CFPB scrutiny is moving from theoretical to examination-ready. PCG has worked inside FS operations, not just advised from outside.
Insurance
Pricing model fairness and underwriting bias are where state regulators are landing. NAIC AI Model Bulletin compliance is in flight but not yet operationalized at most carriers. The governance gap here is acute and largely unaddressed.
Healthcare
Clinical decision support safety and HIPAA compliance for AI systems sit at the intersection of patient risk and regulatory exposure. Prior authorization automation is under Congressional scrutiny. PCG's Fortune 15 healthcare anchor relationship was built in this environment.
Medical Device
FDA's posture on AI/ML Software as a Medical Device (SaMD) is moving fast. Predetermined change control plans and post-market surveillance of AI models are requirements, not options. Very few firms know how to build governance inside a design-controlled environment.
Banking
AML/BSA model accountability and fair-access lending decisions are examiner-ready requirements. Branch and contact-center AI is where the operational readiness gap shows up most visibly.
Retail
Personalization and dynamic pricing fairness are in active regulatory discussion. Workforce scheduling AI under state law is an underappreciated compliance exposure.
Consumer Packaged Goods
Demand forecasting and trade promotion AI have the clearest and fastest ROI case. The operational readiness issue here is data quality, not model quality.
Agriculture
Ag data ownership and privacy is the governance question that's almost entirely unaddressed. Computer vision in crop and livestock operations is moving faster than the operating infrastructure behind it.
Manufacturing
OT/IT convergence security is the governance exposure most plant managers don't know they have. Predictive maintenance ROI is well-established; the operational challenge is integrating AI into legacy plant-floor environments without creating new failure modes.
The question isn't whether AI will transform your industry. It's whether you'll lead that or react to it.
Start the conversation →