Consulting AI Director

Baker Tilly•USA CO Remote, WA

5d•$214,100 - $405,900

About The Position

Baker Tilly is seeking a senior consulting leader with deep applied AI expertise to define and lead the next phase of AI activation across our national consulting business. The firm has already established enterprise AI infrastructure and completed significant use-case identification. The opportunity now is to translate that foundation into a clear vision, an actionable portfolio of priorities, and measurable changes in how consulting services are delivered. This is a business leadership role—not ownership of the underlying AI technology platform or technical delivery organization. The Director must bring enough technical depth to engage credibly with architects, engineers, data professionals, security teams, and platform owners; critically evaluate proposed approaches; challenge assumptions, estimates, constraints, and tradeoffs; and direct technical requests toward the business outcomes Consulting requires. The role will partner closely with the team responsible for OpenAI Enterprise (Anthropic and other tools in consideration), ensuring that technical decisions reflect real consulting workflows, economics, priorities, and adoption needs. The successful candidate will combine consulting-business fluency, deep applied understanding of modern AI, strategic vision, commercial acumen, rigorous critical thinking, and strong executive influence. They will help practice leaders distinguish meaningful advances from market noise, envision new delivery models, understand revenue and margin implications, and prepare the consulting workforce for sustained change. They must also be comfortable constructively challenging technical teams when recommendations are insufficiently grounded in business value, user needs, practicality, or scale.

Requirements

Bachelor’s degree required; advanced degree or relevant professional credential preferred.
12+ years of experience in consulting, professional services, AI-enabled transformation, digital strategy, operating-model design, or a closely related field.
Demonstrated experience applying AI to redesign business processes, knowledge work, service delivery, or professional workflows—not solely managing technology implementation.
Strong understanding of consulting or professional-services economics, including pricing, utilization, leverage, capacity, revenue growth, and profitability.
Proven ability to develop strategy, build business cases, prioritize a portfolio of opportunities, and move initiatives from concept through adoption and scale.
Deep working knowledge of modern AI technologies and solution patterns, including generative AI, large language models, retrieval-augmented generation, agents, data and integration requirements, model limitations, evaluation, security, and human oversight.
Demonstrated ability to engage architects, engineers, data professionals, and platform teams; frame effective technical requests; evaluate proposed approaches and estimates; identify gaps or weak assumptions; and constructively challenge technical recommendations.
Exceptional critical-thinking and decision-making skills, including the ability to synthesize incomplete information, assess competing alternatives, distinguish genuine constraints from organizational preferences, and connect technical choices to business consequences.
Executive-level communication, facilitation, and stakeholder-influence skills, including the ability to communicate complex AI and technology concepts in practical business terms.
Experience partnering across business, technology, risk, legal, security, learning, and change-management functions.
Strong judgment regarding responsible AI, data sensitivity, client confidentiality, intellectual property, human review, and quality control.

Nice To Haves

Leadership experience within a large, multi-service consulting or professional-services organization.
Demonstrated experience with enterprise generative AI platforms such as OpenAI Enterprise, (Anthropic and other tools in consideration), custom GPTs, AI agents, knowledge retrieval, workflow automation, or related capabilities.
Experience creating or scaling AI-enabled offerings, delivery methods, accelerators, centers of excellence, champion networks, or enterprise adoption programs.
Experience leading broad workforce enablement, knowledge-management, or capability-building initiatives.
A visible body of applied work, measurable outcomes, or thought leadership demonstrating the ability to turn AI possibilities into sustained business value.

Responsibilities

Set the vision and activation strategy: Define and communicate a compelling vision for how AI should reshape Baker Tilly Consulting over the near, medium, and longer term. Translate firm strategy, market developments, and identified use cases into a prioritized Consulting AI roadmap with clear sequencing, dependencies, investment needs, and success measures. Advise consulting executives and practice leaders on where to experiment, scale, pause, or redirect effort based on business value, feasibility, risk, and organizational readiness. Maintain a strong external perspective on advances in generative AI, agentic systems, knowledge technologies, and emerging delivery models, separating durable signals from short-lived hype.
Reimagine consulting services and economics: Partner with practice leaders and subject-matter experts to redesign service delivery, workflows, team structures, and client-value propositions around AI-enabled ways of working. Identify opportunities beyond labor efficiency, including improved quality and consistency, just-in-time staff training, stronger knowledge retention and dissemination, accelerated onboarding, enhanced judgment, and scalable access to expertise. Evaluate the implications of AI-enabled delivery for pricing, revenue growth, capacity, utilization, leverage models, profitability, intellectual property, and competitive differentiation. Develop business cases and decision frameworks that connect AI investments to measurable service-line and firm outcomes. Help convert high-value concepts into repeatable methods, accelerators, playbooks, and operating capabilities that can be adopted across practices.
Direct business-to-technology translation and challenge: Serve as the primary Consulting business counterpart to the teams that manage enterprise AI platforms, data, integrations, security, architecture, and technical delivery. Convert consulting opportunities into clear, well-structured technical and capability requests, including business requirements, workflow context, priorities, use cases, data needs, integration needs, adoption expectations, constraints, and measurable outcomes. Apply sufficient technical depth to assess proposed architectures and delivery approaches, ask incisive questions, surface hidden assumptions, evaluate tradeoffs, and challenge recommendations that do not adequately address consulting-business needs. Hold technology partners accountable for translating technical possibilities and limitations into clear business implications, options, risks, costs, dependencies, and decisions. Coordinate with technology, innovation, risk, legal, information security, learning, and other enterprise functions to advance initiatives with appropriate controls and accountability.
Drive adoption and workforce readiness: Align the Consulting AI strategy with the firm’s broader workforce upskilling, learning, talent, and change strategies. Define role-based AI capability expectations for consulting professionals, managers, leaders, specialists, and AI champions. Guide the development of practical enablement approaches, including embedded learning, workflow-based training, communities of practice, reusable knowledge assets, office hours, and leader communications. Build and mobilize a network of practice leaders, implementation leads, power users, and advocates who can translate the strategy into local action. Promote responsible experimentation while reinforcing appropriate human review, professional judgment, confidentiality, quality, and risk management.
Create operating discipline and measurable progress: Establish a practical intake, prioritization, pilot, measurement, and scale process for Consulting AI initiatives. Define scorecards and KPIs that measure adoption, service-delivery impact, quality, workforce capability, revenue contribution, margin effects, and progress from pilot to scaled use. Provide clear, decision-oriented updates to Consulting leadership on progress, barriers, risks, investment needs, and business outcomes. Capture lessons learned and success stories, and use them to accelerate adoption across service lines without creating unnecessary bureaucracy.