Applied AI Process Consultant

You produce solid analytical work — assessing trends and forces shaping your industry or function, designing future-state processes, and building the supporting materials that help senior practitioners shape transformation recommendations. You're developing real expertise in your domain and a point of view on how AI and automation can change the way it operates. You're comfortable working with structured guidance while taking on more with each engagement.

You understand that designing how AI agents interact within processes — AX Design — is just as important as the process design itself, and you're starting to apply those principles in your work.

THE WORK Utilize relevant AI tools across all tasks and deliverable creation, including the creation of agents and other tools to help facilitate: Build and validate analytical frameworks — trend analyses, benchmarking outputs, change-impact assessments — using AI-assisted tools; apply GenAI and LLM tools to accelerate insight synthesis and workflow documentation, evaluating where agentic approaches could automate analytical tasks within process redesign work.

Develop working knowledge of RAG architecture fundamentals — what retrieval-augmented generation is, when it's appropriate, and what its limitations are — sufficient to contribute credibly to AI-integrated process design discussions and specification work. Design insight outputs and process documentation with an information and UX design mindset — considering how process stakeholders will read, interpret, and act on what you produce; structure narratives clearly and tailor them to the audience.

Apply responsible design standards to every output: validate for bias and explainability, define where human-in-the-loop oversight is required, and specify escalation triggers and handoff points clearly in any process design that incorporates AI or agentic components. Produce trend and forces assessments for your assigned industry or function, including benchmarking analyses that show where the client stands relative to peers and where the reinvention opportunity lies.

Design future-state process specifications covering AI integration points, operating model changes, human-machine interaction requirements, and workforce adoption approaches for your domain area. Conduct process analysis and support delivery of digital and platform solutions across operations. Apply your industry or function knowledge to review and improve domain-specific reinvention designs and functional playbook content. Contribute to the reference library and keep your domain expertise current through continuous learning.

Apply AX Design principles when specifying or reviewing AI integration designs — defining how AI agents should behave within each redesigned process step, what they handle autonomously, and when they hand off to a person. EDUCATION Bachelor's Degree or equivalent
BASIC (REQUIRED) QUALIFICATION Experience in process excellence, process redesign, or management consulting
Experience producing industry or function trend analyses, benchmarking outputs, or change-impact assessments
Previous usage of AI-assisted analytics, visualization, or benchmarking tools (e.g.

Platform Native AI capabilities)
Experience integrating AI and automating business process design
You have previously delivered project work in consulting environment OR industry experience in at least one domain (e.g., Banking/Capital Markets, Insurance, Software and Platforms, Communications and Media, High Tech, Health, Public Service, Life Sciences, Consumer Goods Retail and Travel, Industrial, Energy, Utilities or Chemical and Natural Resources) OR worked within
Ability to analyze data and translate findings into structured recommendations
PREFERRED QUALIFICATION Familiarity with process mapping or process modeling tools
Strong analytical skills with the ability to communicate complex findings in clear business terms/structured recommendations
Client-facing consulting or advisory experience
Applies AI tools fluently and independently, including building agents, for higher-quality deliverables to business problems
Embeds AI Design principles into process specifications (agent behaviors, autonomy levels, handoffs)
Identifies where agentic AI can transform specific client process steps and articulates design implications
Uses AI-assisted analytics, visualization, and benchmarking tools to ground future-state designs
Demonstrated continuous learning with emerging AI tools
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