Associate Director, Corporate Strategy- Enterprise AI Transformation

The AI TO is responsible foraccelerating and scaling responsible AI adoption across Wolters Kluwer by helping functions identifyhigh-value opportunities, reinvent workflows, coordinate enabling resources, govern risk, and deliver measurable business impact. Functions and business owners remainaccountable for execution, adoption, and outcomes; the AI TO provides the rigor, expertise, visibility, and support requiredto accelerate progress.

The Associate Director role will work closely with functional leaders, business owners, Finance, Data, Technology, HR, and other stakeholders todeterminewhere AI can materially improve business performance and to build the fact baserequiredto make investment and scaling decisions.

The successful candidate will translate ambiguous questions such as “Could AI fundamentally improve this workflow?”into rigorous, evidence-based answers. This will require understanding how work is performed today, identifyingthe operational and financial drivers of performance, establishingcredible baselines, defining the right KPIs, quantifying value at stake, pressure-testing assumptions, and measuring whether expected value is ultimately realized.

This is a hands-on strategy and analytics role. The ideal candidate combines the structured problem solving and business judgment of a strategy consultant with a strong quantitative orientation and a willingness to dig deeply into data, processes, assumptions, and economics.

Primary Accountabilities

Identifyand diagnose high-value opportunities

• Partner with functional leaders, process owners, and frontline subject-matter experts to understand how work is performed today and where AI-enabled workflow redesign could materially improve business outcomes.

• Conduct business and process diagnostics to identifybottlenecks, sources of cost, delays, capacity constraints, quality issues, risk, or lost revenue.

• Help distinguish incremental productivity opportunities from more transformational opportunities to redesign end-to-end workflows around human judgment, AI agents, data, and automation.

• Assess the scale and materiality of opportunities and identifythe key value drivers that determinewhether an initiative merits investment.

Define KPIs and establishcredible baselines

• Translate broad transformation ambitions into a small number of meaningful business and operational KPIs.

• Determinehow relevant measures are calculated today, where the underlying data resides, who owns it, and what constitutes a credible baseline.

• Gather, reconcile, and analyze information across multiple sources to establishcurrent performance, including volumes, cycle times, throughput, productivity, quality, conversion, capacity, costs, customer outcomes, and other relevant measures.

• Identifydata gaps, limitations, and assumptions and develop pragmatic approaches for measuring performance where perfect data is not available.

• Ensure initiatives have measurable success criteria before investment and implementation decisions are made.

Quantify value at stake

• Build transparent, driver-based models that translate changes in operational performance into financial and strategic outcomes.

• Quantify potential value from revenue growth, productivity, capacity creation, cost reduction, quality improvement, risk reduction, customer impact, or employee experience as appropriate.

• Develop Year 1 and longer-term value estimates, expected operating costs, requiredinvestment, and net business impact.

• Clearly distinguish between cash savings, capacity released, cost avoidance, revenue improvement, and other forms of value.

• Document the critical assumptions behind each value case and identifythe sensitivities that have the greatest effect on expected outcomes.

Develop and challenge business cases

• Develop rigorous, directional business cases for priority AI opportunities, considering value, feasibility, investment, risk, readiness, adoption, and implementation complexity.

• Pressure-test assumptions and challenge sponsors and business owners constructively where supporting evidence is weak.

• Identifythe critical conditions that must be true for an initiative to deliver its expected value.

• Compare opportunities consistently to help leadership prioritize limited investment and execution capacity.

• Support build / buy / partner analysis where relevant, incorporating expected economics, differentiation, operating costs, and dependencies.

Design value measurement and evaluate results

• Define measurement approaches for pilots and scaled deployments, including baseline, target, leading indicators, operational KPIs, business outcomes, and measurement cadence.

• Establish the analytical bridge between AI adoption, workflow change, operational performance, and financial impact.

• Compare realized results with expected performance and diagnose the causes of variance.

• Determinewhether evidence supports scaling, modifying, pausing, or stopping an initiative.

• Partner with Finance and business owners to ensurerealized value is credible, traceable, and understood consistently.

Build the enterprise AI value view

• Aggregate opportunity-level analyses into a transparent enterprise view of expected and realized AI value.

• Identifythe largest emerging value pools, material assumptions, risks, dependencies, and gaps across the AI portfolio.

• Provide leadership with fact-based perspectives on where the enterprise is creating value, where performance is falling short, and where additionalintervention or investment is required.

• Help maintainclear accountability for business outcomes and KPI movement across priority initiatives.

Generate executive insight and recommendations

• Lead analyses across multiple sources of quantitative and qualitative information; identifymeaningful patterns, test hypotheses, surface limitations, and translate findings into practical recommendations.

• Develop concise, executive-ready decision materials for the AI TO, functional leadership, Executive Leadership Team, and other senior stakeholders.

• Communicate complex analyses simply, clearly articulating the answer, supporting evidence, implications, and recommended actions.

• Independently lead analytical workstreams from problem definition through recommendation.

Build repeatable approaches and institutional capability

• Develop practical frameworks, templates, benchmarks, and analytical tools that allow AI opportunities to be evaluated consistently across functions.

• Capture learnings from initiatives and continuously improve the AI TO's value-realization methodologyand operating routines.

• Monitor emerging approaches to AI economics, measurement, workflow transformation, and value realization and selectively incorporate relevant practices into the AI TO playbook.

Skills and Competencies

• Exceptional structured problem-solving skills and ability to turn ambiguous business questions into clear hypotheses, analyses, and recommendations.

• Strong quantitative and analytical orientation, including demonstratedability to build driver-based business and financial models from imperfect or incomplete information.

• Strong business judgment and ability to identifythe few metrics and value drivers that matter most.

• Ability to quickly understand unfamiliar business processes, operating models, and economics.

• Intellectual curiosity and willingness to dig deeply into source data, process details, assumptions, and calculations.

• Strong understanding of the relationship between operational performance and financial outcomes.

• Ability to synthesize quantitative and qualitative information into clear implications and recommendations.

• Excellent written and verbal communication skills, including the ability to create concise, executive-ready materials.

• Strong interpersonal skills and ability to build credibility with senior leaders, functional stakeholders, Finance, technical teams, and frontline subject-matter experts.

• Confidence constructively challenging assumptions while maintainingproductive stakeholder relationships.

• Strong ownership mindset and ability to independently lead complex analytical workstreams.

• Experience using generative AI tools to accelerate research, analysis, synthesis, and problem solving preferred.

• Familiarity with BI tools, SQL, or other analytical tools is helpful but not required.

Qualifications

• Bachelor's degree in business, economics, finance, engineering, analytics, or a related quantitative discipline; advanced degree preferred but not required.

• 5+ years of experience in strategy consulting, corporate strategy, strategic finance, transformation, performance improvement, or a similarly rigorous analytical environment.

• Strong preference for candidates with experience at a leading strategy or management consulting firm, particularly in business diagnostics, commercial due diligence, corporate finance, performance improvement, or transformation.

• Demonstrated experience developing analytical models, defining KPIs, establishingperformance baselines, assessing business opportunities, and translating operational improvements into financial impact.

• Experience synthesizing complex information from multiple sources and developing senior-management recommendations.

• Ability to rapidly develop a working understanding of unfamiliar functions, industries, and business processes.

• Experience in B2B technology, software, information services, or professional services preferred.

• Prior experience with AI transformation or emerging technology is helpful, but deep technical AI expertise is not required.

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we’re getting to know you-not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.

Compensation:

Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process.

Additional Information:

Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.