AI Business Strategy Consultant

Position is open for multiple locations, Waltham, Boston, Syracuse, Hicksville, Melville, Brooklyn any NY Office location is fine but will be on a Hybrid model. 2 -3 days at office.

Job Purpose:

The AI Value Office Consultant is a US-based individual-contributor role responsible for helping business teams identify, shape, assess and progress high-value artificial intelligence opportunities. Reporting to the AI Value Office Director, the role operates as a hands-on internal consultant and a key Value Office interface for relevant US business stakeholders, while working as part of one integrated UK/US team.

The Consultant supports opportunities through the end-to-end AI value lifecycle: origination and intake, problem framing, value and feasibility assessment, business-case development, prioritization, delivery partnership and value realization. The role works closely with Connect AI and other delivery teams to translate business needs into clear requirements, assess build, buy and reuse options, identify the best-fit delivery route and maintain focus on measurable outcomes. Technical design, engineering and solution ownership remain with the appropriate delivery teams.

The Consultant is responsible for rigorous analysis and accurate reporting at opportunity level, including financial and non-financial benefits, costs, assumptions, baselines, KPIs, benefit ownership, adoption and risk. Portfolio-level ownership and executive accountability remain with the AI Value Office Director and Head of AI Value Office.

Key Outcomes
Success in this role will be measured by:

A strong pipeline of strategically aligned and well-defined US AI opportunities.
Clear problem statements, business sponsorship, value hypotheses and success measures for assigned opportunities.
High-quality financial and non-financial business cases that support timely prioritization and investment decisions.
Effective collaboration with Connect AI and other delivery teams to assess feasibility and determine the right solution and delivery route.
Accurate tracking of value through forecast/identified, agreed/approved and achieved/realized stages.
Transparent, timely reporting on progress, value, adoption, risks, dependencies and required decisions.
Strong relationships with US business, Finance, technology and governance stakeholders.
Consistent application and continuous improvement of Value Office methods, templates and controls.
Section 3 - Key Accountabilities
Opportunity Origination, Intake and Problem Framing
Build trusted-advisor relationships with US business stakeholders and develop a practical understanding of their strategic priorities, processes and pain points.
Proactively identify and shape AI opportunities through interviews, workshops, process analysis and review of existing transformation roadmaps.
Support the single-front-door intake and triage process, ensuring each opportunity has a clearly defined problem, business owner, sponsor, intended outcome and initial value hypothesis.
Assess strategic alignment, potential impact, delivery readiness, data readiness, risk, dependencies and reuse potential.
Prepare clear recommendations on whether an opportunity should proceed, be refined, paused, consolidated or routed to another capability.
Maintain accurate opportunity records, actions, decisions and supporting evidence throughout the lifecycle.
Value Assessment and Business Cases
Develop robust financial and non-financial value cases, including expected benefits, costs, assumptions, baselines, timelines, KPIs, benefit owners, adoption measures, risks and dependencies.
Work with Finance and business stakeholders to validate material assumptions, baselines, forecasts and measurement approaches.
Distinguish clearly between direct financial value, productivity and cost avoidance, operational improvements, customer outcomes, regulatory/risk/safety benefits and strategic value.
Use agreed Value Office methods and templates to ensure consistency and comparability across opportunities.
Prepare concise materials for prioritization, funding, sanction and investment decisions.
Update business cases as evidence develops and maintain a clear record of changes to scope, value, costs and assumptions.
Solution Shaping and Delivery Partnership
Work with Connect AI, Architecture, Data, Technology, Responsible AI, vendors and business subject-matter experts to translate business problems into clear solution requirements and options.
Support assessment of technical feasibility, data availability, integration requirements, delivery complexity, risk and total cost of ownership.
Identify potential duplication and opportunities to reuse existing enterprise platforms, products, models, agents, data assets and vendor capabilities.
Support build, buy, configure and reuse assessments and provide evidence for the recommended delivery route.
Agree success measures and a value-measurement plan with business and delivery stakeholders before handoff.
Act as the business-facing interface for assigned opportunities during discovery and delivery, while leaving technical design and engineering accountability with the relevant delivery team.
Monitor delivery from a value and outcomes perspective and escalate material changes that may affect the business case or expected benefits.
Value Tracking, Reporting and Realization
Track assigned opportunities through forecast/identified value, agreed/approved value and achieved/realized value.
Maintain accurate portfolio data covering status, value, costs, milestones, KPIs, adoption, risks, dependencies and decisions.
Work with business benefit owners and Finance to gather evidence and validate realized outcomes where appropriate.
Monitor performance against approved business cases and identify value leakage, delayed adoption, unsupported assumptions or delivery risks.
Prepare concise dashboards, reports, presentations and decision materials for the Director, Head of AI Value Office and senior stakeholders.
Support post-implementation reviews, lessons learned, success stories and recommendations to scale, remediate, pivot or close initiatives.
Governance, Risk and Continuous Improvement
Ensure assigned opportunities follow agreed governance, stage gates, investment controls and record-keeping requirements.
Collaborate with Responsible AI, Data Governance, Legal, Security, Risk, Compliance and Architecture teams to support relevant assessments and controls.
Ensure material risks, dependencies and control requirements are visible in value cases and reporting.
Contribute to the improvement of Value Office methodologies, templates, playbooks, dashboards and stakeholder-engagement practices.
Share knowledge and reusable insight across the UK/US Value Office and wider Connect AI community.
Support the Director and Head of AI Value Office with portfolio analysis and implementation of agreed AI strategy and operating-model priorities.

Required Experience
Experience in management consulting, internal consulting, business analysis, digital transformation, technology strategy, analytics or AI advisory.
Proven experience framing complex business problems, capturing requirements and translating them into structured opportunities and recommendations.
Experience developing business cases, investment proposals, benefits frameworks, KPIs and value-realization plans.
Experience working across business, Finance, technology, data, risk and delivery teams in a matrixed organization.
Strong track record of preparing and delivering clear presentations, reports and recommendations for senior stakeholders.
Ability to work independently, manage multiple priorities and influence without direct authority.
Experience in utilities, energy or another complex, regulated or asset-intensive industry is desirable.

Knowledge & Expertise
Good understanding of analytics, artificial intelligence, machine learning, generative AI, automation and agentic AI, and how they can support business objectives.
Understanding of the AI lifecycle from discovery and validation through build, deployment, adoption and value realization.
Business analysis, process analysis, opportunity assessment and requirements-shaping methods.
Financial and non-financial value assessment, including costs, benefits, ROI, total cost of ownership, assumptions, baselines and KPIs.
Awareness of build, buy, configure and reuse considerations and different delivery models.
Working knowledge of data readiness, enterprise architecture, information security, Responsible AI and technology risk.
Sufficient technical literacy to challenge assumptions and work effectively with specialists, without being a hands-on data scientist, engineer or solution architect.

Professional Capabilities
Structured problem-solving and evidence-based judgment.
Commercial and financial acumen.
Clear written, verbal and visual communication.
Workshop facilitation, stakeholder engagement and executive presence.
Collaboration across cultures, functions and geographies.
Attention to detail, quality assurance and disciplined follow-through.
Curiosity, adaptability and commitment to continuous learning.

Section 5 - Qualifications
Essential (at appointment): Bachelor’s degree in Computer Science, Engineering, Data Science, Statistics, Economics, Business Management or a related field, or equivalent relevant professional experience.
Experience expectation: Typically 5+ years of relevant experience with a Master’s degree, or 7+ years with a Bachelor’s degree, consistent with the existing US specialist profile. Equivalent combinations of education and experience may be considered.
Desirable: Master’s degree; relevant consulting, business analysis, finance, portfolio, change, data or AI-related professional qualifications.

Section 6 - Job Dimensions
Number of Direct/Indirect Reports: Individual contributor; no direct reports.
Budget: No direct budget accountability specified.
Other: US-based role working across relevant US business areas and collaborating with the UK Value Office as part of one global team. Travel requirements: TBC.

Section 7 - Main Interfaces
AI Value Office Director.
Head of AI Value Office and UK/US Value Office colleagues.
US Business Unit and Group Function leaders, sponsors, business owners and subject-matter experts.
Connect AI / AI Delivery, Data Science, Engineering and product teams.
Finance and Finance Business Partners.
Data, Technology, Enterprise Architecture, Platforms, Cloud and Security teams.
Responsible AI, Risk, Legal, Compliance and Data Governance teams.
Procurement, Commercial, vendor-management and external partner teams.
Change, adoption, communications and operational teams responsible for embedding solutions and sustaining benefits.

Leadership Qualities & Business Skills

Technical Competencies:
AI opportunity assessment and problem framing.
Business analysis and requirements shaping.
Value-case development and benefits realization.
Financial and non-financial value analysis.
Portfolio data, KPI tracking and performance reporting.
Solution-option and delivery-route assessment.
AI lifecycle, Responsible AI and technology-risk awareness.

Business Capabilities
Performance Excellence: Applies consistent methods, maintains high-quality records and tracks outcomes against agreed KPIs and milestones.
Contract Management: Supports evaluation of supplier and commercial options and monitors agreed deliverables where required.
Stakeholder Engagement: Builds trusted relationships, facilitates alignment and communicates effectively with business, technology and senior stakeholders.
Project Management: Coordinates actions, decisions, risks, dependencies and value milestones across multiple opportunities.
Commerciality: Develops credible business cases and challenges costs, benefits, assumptions and sourcing options.
Customer: Provides a responsive, outcome-focused internal consulting service to business stakeholders.
Data Management: Understands how data availability, quality, access and governance affect AI feasibility and value.
Advanced Analytics: Uses sufficient analytics and AI literacy to assess opportunities and work effectively with technical specialists.
Asset Management: Understands or develops knowledge of the operational and asset-intensive context in which enterprise AI value is created.