Mastering AI-Driven Strategy for Future-Proof Leadership
You're not behind because you're not trying hard enough. You're behind because the rules of leadership changed overnight - and no one handed you the new playbook. While others confidently present AI-powered strategies to executives, you're left decoding jargon, second-guessing frameworks, and wondering if your next decision will be obsolete by quarter's end. The pressure is real. Boards demand AI fluency. Investors reward speed and precision. Peers are already launching AI initiatives that cut costs by 30% or unlock entirely new revenue streams. Meanwhile, you're balancing legacy systems, team resistance, and the constant fear that you're missing the signal in the noise. Mastering AI-Driven Strategy for Future-Proof Leadership isn't another theory-heavy course. It's your step-by-step system to go from uncertain to authoritative in exactly 30 days. By day 30, you’ll have built a fully validated, board-ready AI strategy for your organisation - one that aligns with business objectives, leverages the right data, and delivers measurable ROI. Take Sarah Chen, Principal Strategy Lead at a Fortune 500 healthcare provider. After completing this course, she led a cross-functional team to deploy an AI-driven patient triage model that reduced wait times by 42% and freed up $2.1M in annual operational costs. Her CEO called it “the most actionable strategy proposal we’ve seen in five years.” She was promoted six months later. This isn’t about becoming a data scientist. It’s about mastering the leadership mindset, strategic frameworks, and execution workflows that turn AI from a buzzword into a boardroom advantage. You’ll learn how to prioritise high-impact use cases, secure buy-in, mitigate risk, and scale what works - all without needing to write a single line of code. No fluff. No filler. Just a proven path to being the leader your organisation turns to when it’s time to lead through disruption. Here’s how this course is structured to help you get there.Course Format & Delivery Details Self-Paced, On-Demand Learning Designed for Real Leaders
This course is designed for executives, senior managers, and strategic leaders who need clarity, not clutter. You get immediate online access, self-paced progression, and no fixed dates or time commitments. Whether you have 45 minutes at 5 a.m. or two hours on a redeye flight, progress happens on your terms. Most participants complete the core curriculum in under 12 weeks, with many presenting their first AI strategy proposal within 30 days. The fastest learners - those who apply one module per week - finish the full certification path in 8 weeks, with tangible results visible by week 3. Lifetime Access, Continuous Updates, Zero Extra Cost
- You get lifetime access to all course materials, including every future update. AI evolves rapidly, and so does this course. New frameworks, tools, and regulatory insights are added quarterly - no subscription, no extra fees.
- All content is mobile-friendly and accessible 24/7 from any device. Review strategy templates on your phone, download toolkit PDFs on your tablet, or work through scenario exercises on your laptop in offline mode.
- You are not alone. You’ll receive direct instructor support via structured feedback loops, curated responses to common implementation roadblocks, and access to expert-vetted solution pathways for complex organisational challenges.
Certification That Commands Respect
Upon successful completion, you’ll earn a Certificate of Completion issued by The Art of Service - a globally recognised credential trusted by over 12,000 organisations in 97 countries. This isn’t a participation trophy. It’s proof you’ve mastered the methodology to design, validate, and lead AI-driven strategy in real-world environments. Employers, boards, and clients recognise this standard - and treat it as evidence of leadership capability in digital transformation. No Hidden Fees. No Surprise Costs. Ever.
Pricing is straightforward and one-time. There are no hidden fees, no auto-renewals, and no upsells. What you pay today is all you pay, for life. We accept Visa, Mastercard, and PayPal - all processed securely with bank-grade encryption. Zero-Risk Enrollment: Satisfied or Refunded
You’re protected by our unconditional money-back guarantee. If you complete the first three modules and don’t feel a significant gain in clarity, confidence, and strategic control, simply request a full refund. No questions, no hoops, no risk. “Will This Work for Me?” We’ve Got You Covered.
You might be thinking: I’m not technical. I don’t lead an AI team. My industry is too regulated. My company moves too slowly. This works even if you’ve never led a digital transformation, your technical team is stretched thin, or you’re operating in a heavily audited environment like finance, healthcare, or government. The framework is designed for cross-functional alignment, compliance-aware delivery, and stakeholder persuasion - not technical dependency. Our learners include legal counsels who’ve embedded AI governance into procurement, supply chain directors who automated demand forecasting, and HR VPs who deployed ethical AI for talent retention. The common thread? They didn’t need to code. They needed a repeatable process - and now they have one. After enrollment, you’ll receive a confirmation email. Once the course materials are prepared, your secure access details will be sent separately. This ensures a clean onboarding process, data protection, and a seamless start to your learning journey.
Extensive and Detailed Course Curriculum
Module 1: The Strategic Imperative of AI in Modern Leadership - Why traditional strategy frameworks fail in AI-driven environments
- The 5 leadership archetypes in the AI era - and which one leads change
- How AI is reshaping competitive advantage across industries
- Understanding the AI maturity curve in enterprises
- The 3-second rule: How stakeholders now judge strategic relevance
- Recognising AI hype vs. high-impact use cases
- Building your personal AI fluency baseline
- Establishing your leadership foothold in digital transformation
- Mapping AI capability to business value chains
- Case study: How a regional bank outmanoeuvred fintech competitors using AI strategy
Module 2: Foundations of AI-Driven Strategic Thinking - The 7 core principles of AI-augmented decision-making
- Decoupling technical complexity from strategic value
- How to think like an AI strategist - not an engineer
- The signal-to-noise ratio in data-rich environments
- Understanding supervised, unsupervised, and reinforcement learning at a leadership level
- Natural language processing, computer vision, and generative AI - what they mean for business
- Differentiating between automation, optimisation, and innovation AI
- Time horizons for AI impact: short, mid, and long-term value
- Defining AI readiness in your organisation
- The leadership mindset shift: from control to orchestration
Module 3: The Future-Proof Leadership Framework - Introducing the F.L.A.R.E. model: Forecast, Lead, Adapt, Respond, Evolve
- How to future-proof your strategic planning process
- The 3 layers of AI resilience in leadership
- Building adaptability into organisational DNA
- Scenario planning for AI disruption and opportunity
- Stress-testing your strategy against emerging technologies
- Creating feedback loops that accelerate learning
- Measuring strategic agility and leadership responsiveness
- Developing organisational immunity to obsolescence
- Transitioning from reactive to anticipatory leadership
Module 4: Strategic Prioritisation of AI Use Cases - The AI Opportunity Matrix: Value vs. feasibility scoring
- Using the IDEA filter: Impact, Data, Effort, Alignment
- Identifying low-hanging fruit with high visibility
- Avoiding the “shiny object” trap in AI selection
- How to conduct a 90-minute AI opportunity workshop with your team
- Prioritising use cases by board-level relevance
- Aligning AI initiatives with ESG, compliance, and risk mandates
- Mapping AI to customer journey pain points
- Calculating potential ROI for operational and revenue AI
- Case study: From 47 ideas to 3 board-approved pilots
Module 5: Data Strategy for Non-Technical Leaders - The leadership role in data governance and quality
- Understanding data pipelines without technical jargon
- How to ask the right questions about data readiness
- Evaluating internal vs. external data sourcing
- Establishing data ownership and stewardship
- Minimum viable data: What you need to start
- Identifying data silos and integration barriers
- Assessing data bias and fairness at scale
- Building trust in data across departments
- Creating a data strategy communication plan
Module 6: The AI Stakeholder Alignment Protocol - The 6 key stakeholder archetypes in AI projects
- How to speak to legal, compliance, and risk teams confidently
- Tailoring your message for technical versus non-technical audiences
- Running alignment workshops with cross-functional teams
- The 3-part persuasion framework: Problem, Path, Payoff
- Overcoming resistance with psychological safety techniques
- Using pre-mortems to surface concerns early
- Creating shared ownership of AI initiatives
- Building coalition champions across departments
- Measuring stakeholder buy-in progress
Module 7: Designing the Board-Ready AI Proposal - The 5 essential components of every AI strategy document
- Structuring your proposal for executive attention
- How to open with strategic urgency, not technical detail
- Presenting risk mitigation plans that reassure
- Using the SLIDE format: Situation, Leverage, Investment, Delivery, Evidence
- Creating compelling visual summaries for time-poor leaders
- Anticipating and answering the 7 most common board questions
- Aligning with financial planning cycles and budget gates
- Building phased rollout plans with quick wins
- Template: Executive AI strategy proposal (customisable)
Module 8: Risk, Ethics, and Governance in AI Strategy - The 4 ethical red lines in enterprise AI
- Establishing AI governance committees
- Designing for transparency and explainability
- Managing model drift and performance degradation
- Compliance with global AI regulations and frameworks
- Conducting AI impact assessments
- Implementing human-in-the-loop oversight
- Handling data privacy and consent in AI workflows
- Creating AI incident response protocols
- Building public trust in algorithmic decisions
Module 9: The AI Execution Blueprint - The 90-day AI launch sequence
- Assembling the minimum viable team
- Defining success metrics and KPIs
- Setting up feedback loops for early validation
- Running pilot tests with real data and users
- Managing vendor selection and procurement
- Avoiding scope creep in early AI projects
- Documenting decisions and assumptions
- Using rapid iteration to accelerate learning
- Escalating roadblocks using structured escalation paths
Module 10: Measuring and Communicating AI Value - From output to outcome: What really matters in AI ROI
- Quantifying efficiency, revenue, and risk reduction gains
- Creating before-and-after performance snapshots
- Using storytelling to amplify impact
- Reporting progress without technical overcomplication
- Developing internal case studies for broader adoption
- Tracking both leading and lagging indicators
- Updating the board quarterly with confidence
- Adjusting strategy based on real data
- Scaling success: When and how to go enterprise-wide
Module 11: Leading Cross-Functional AI Teams - How to lead without authority in matrix organisations
- Setting psychological safety for AI innovation
- Running effective stand-ups and retrospectives
- Managing conflict between data, tech, and business teams
- Facilitating solution brainstorming sessions
- Delegating AI tasks with clarity and accountability
- Building team trust in ambiguous environments
- Recognising and rewarding contributions publicly
- Managing burnout in high-pressure AI projects
- Developing team AI literacy at all levels
Module 12: Scaling AI Across the Organisation - The 3 phases of AI adoption: pilot, expand, entrench
- Creating an AI centre of excellence
- Developing internal AI champions
- Building reusable templates and playbooks
- Establishing AI project intake and prioritisation
- Integrating AI into existing strategic planning cycles
- Securing sustained funding and resources
- Driving cultural change through visible wins
- Managing resistance at scale
- Measuring organisational AI maturity over time
Module 13: AI Strategy in Regulated and Complex Industries - Tailoring AI strategy for healthcare, finance, and government
- Working within compliance and audit constraints
- Designing for regulator readiness
- Documentation standards for auditable AI
- Handling third-party model risk
- Ensuring algorithmic fairness in high-stakes decisions
- Conducting external validation and peer review
- Navigating procurement rules for AI vendors
- Managing legacy system integration challenges
- Case study: Deploying AI in a Tier 1 bank under Basel III
Module 14: The Leader’s Toolkit: Templates, Checklists, and Workflows - AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
Module 1: The Strategic Imperative of AI in Modern Leadership - Why traditional strategy frameworks fail in AI-driven environments
- The 5 leadership archetypes in the AI era - and which one leads change
- How AI is reshaping competitive advantage across industries
- Understanding the AI maturity curve in enterprises
- The 3-second rule: How stakeholders now judge strategic relevance
- Recognising AI hype vs. high-impact use cases
- Building your personal AI fluency baseline
- Establishing your leadership foothold in digital transformation
- Mapping AI capability to business value chains
- Case study: How a regional bank outmanoeuvred fintech competitors using AI strategy
Module 2: Foundations of AI-Driven Strategic Thinking - The 7 core principles of AI-augmented decision-making
- Decoupling technical complexity from strategic value
- How to think like an AI strategist - not an engineer
- The signal-to-noise ratio in data-rich environments
- Understanding supervised, unsupervised, and reinforcement learning at a leadership level
- Natural language processing, computer vision, and generative AI - what they mean for business
- Differentiating between automation, optimisation, and innovation AI
- Time horizons for AI impact: short, mid, and long-term value
- Defining AI readiness in your organisation
- The leadership mindset shift: from control to orchestration
Module 3: The Future-Proof Leadership Framework - Introducing the F.L.A.R.E. model: Forecast, Lead, Adapt, Respond, Evolve
- How to future-proof your strategic planning process
- The 3 layers of AI resilience in leadership
- Building adaptability into organisational DNA
- Scenario planning for AI disruption and opportunity
- Stress-testing your strategy against emerging technologies
- Creating feedback loops that accelerate learning
- Measuring strategic agility and leadership responsiveness
- Developing organisational immunity to obsolescence
- Transitioning from reactive to anticipatory leadership
Module 4: Strategic Prioritisation of AI Use Cases - The AI Opportunity Matrix: Value vs. feasibility scoring
- Using the IDEA filter: Impact, Data, Effort, Alignment
- Identifying low-hanging fruit with high visibility
- Avoiding the “shiny object” trap in AI selection
- How to conduct a 90-minute AI opportunity workshop with your team
- Prioritising use cases by board-level relevance
- Aligning AI initiatives with ESG, compliance, and risk mandates
- Mapping AI to customer journey pain points
- Calculating potential ROI for operational and revenue AI
- Case study: From 47 ideas to 3 board-approved pilots
Module 5: Data Strategy for Non-Technical Leaders - The leadership role in data governance and quality
- Understanding data pipelines without technical jargon
- How to ask the right questions about data readiness
- Evaluating internal vs. external data sourcing
- Establishing data ownership and stewardship
- Minimum viable data: What you need to start
- Identifying data silos and integration barriers
- Assessing data bias and fairness at scale
- Building trust in data across departments
- Creating a data strategy communication plan
Module 6: The AI Stakeholder Alignment Protocol - The 6 key stakeholder archetypes in AI projects
- How to speak to legal, compliance, and risk teams confidently
- Tailoring your message for technical versus non-technical audiences
- Running alignment workshops with cross-functional teams
- The 3-part persuasion framework: Problem, Path, Payoff
- Overcoming resistance with psychological safety techniques
- Using pre-mortems to surface concerns early
- Creating shared ownership of AI initiatives
- Building coalition champions across departments
- Measuring stakeholder buy-in progress
Module 7: Designing the Board-Ready AI Proposal - The 5 essential components of every AI strategy document
- Structuring your proposal for executive attention
- How to open with strategic urgency, not technical detail
- Presenting risk mitigation plans that reassure
- Using the SLIDE format: Situation, Leverage, Investment, Delivery, Evidence
- Creating compelling visual summaries for time-poor leaders
- Anticipating and answering the 7 most common board questions
- Aligning with financial planning cycles and budget gates
- Building phased rollout plans with quick wins
- Template: Executive AI strategy proposal (customisable)
Module 8: Risk, Ethics, and Governance in AI Strategy - The 4 ethical red lines in enterprise AI
- Establishing AI governance committees
- Designing for transparency and explainability
- Managing model drift and performance degradation
- Compliance with global AI regulations and frameworks
- Conducting AI impact assessments
- Implementing human-in-the-loop oversight
- Handling data privacy and consent in AI workflows
- Creating AI incident response protocols
- Building public trust in algorithmic decisions
Module 9: The AI Execution Blueprint - The 90-day AI launch sequence
- Assembling the minimum viable team
- Defining success metrics and KPIs
- Setting up feedback loops for early validation
- Running pilot tests with real data and users
- Managing vendor selection and procurement
- Avoiding scope creep in early AI projects
- Documenting decisions and assumptions
- Using rapid iteration to accelerate learning
- Escalating roadblocks using structured escalation paths
Module 10: Measuring and Communicating AI Value - From output to outcome: What really matters in AI ROI
- Quantifying efficiency, revenue, and risk reduction gains
- Creating before-and-after performance snapshots
- Using storytelling to amplify impact
- Reporting progress without technical overcomplication
- Developing internal case studies for broader adoption
- Tracking both leading and lagging indicators
- Updating the board quarterly with confidence
- Adjusting strategy based on real data
- Scaling success: When and how to go enterprise-wide
Module 11: Leading Cross-Functional AI Teams - How to lead without authority in matrix organisations
- Setting psychological safety for AI innovation
- Running effective stand-ups and retrospectives
- Managing conflict between data, tech, and business teams
- Facilitating solution brainstorming sessions
- Delegating AI tasks with clarity and accountability
- Building team trust in ambiguous environments
- Recognising and rewarding contributions publicly
- Managing burnout in high-pressure AI projects
- Developing team AI literacy at all levels
Module 12: Scaling AI Across the Organisation - The 3 phases of AI adoption: pilot, expand, entrench
- Creating an AI centre of excellence
- Developing internal AI champions
- Building reusable templates and playbooks
- Establishing AI project intake and prioritisation
- Integrating AI into existing strategic planning cycles
- Securing sustained funding and resources
- Driving cultural change through visible wins
- Managing resistance at scale
- Measuring organisational AI maturity over time
Module 13: AI Strategy in Regulated and Complex Industries - Tailoring AI strategy for healthcare, finance, and government
- Working within compliance and audit constraints
- Designing for regulator readiness
- Documentation standards for auditable AI
- Handling third-party model risk
- Ensuring algorithmic fairness in high-stakes decisions
- Conducting external validation and peer review
- Navigating procurement rules for AI vendors
- Managing legacy system integration challenges
- Case study: Deploying AI in a Tier 1 bank under Basel III
Module 14: The Leader’s Toolkit: Templates, Checklists, and Workflows - AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
- The 7 core principles of AI-augmented decision-making
- Decoupling technical complexity from strategic value
- How to think like an AI strategist - not an engineer
- The signal-to-noise ratio in data-rich environments
- Understanding supervised, unsupervised, and reinforcement learning at a leadership level
- Natural language processing, computer vision, and generative AI - what they mean for business
- Differentiating between automation, optimisation, and innovation AI
- Time horizons for AI impact: short, mid, and long-term value
- Defining AI readiness in your organisation
- The leadership mindset shift: from control to orchestration
Module 3: The Future-Proof Leadership Framework - Introducing the F.L.A.R.E. model: Forecast, Lead, Adapt, Respond, Evolve
- How to future-proof your strategic planning process
- The 3 layers of AI resilience in leadership
- Building adaptability into organisational DNA
- Scenario planning for AI disruption and opportunity
- Stress-testing your strategy against emerging technologies
- Creating feedback loops that accelerate learning
- Measuring strategic agility and leadership responsiveness
- Developing organisational immunity to obsolescence
- Transitioning from reactive to anticipatory leadership
Module 4: Strategic Prioritisation of AI Use Cases - The AI Opportunity Matrix: Value vs. feasibility scoring
- Using the IDEA filter: Impact, Data, Effort, Alignment
- Identifying low-hanging fruit with high visibility
- Avoiding the “shiny object” trap in AI selection
- How to conduct a 90-minute AI opportunity workshop with your team
- Prioritising use cases by board-level relevance
- Aligning AI initiatives with ESG, compliance, and risk mandates
- Mapping AI to customer journey pain points
- Calculating potential ROI for operational and revenue AI
- Case study: From 47 ideas to 3 board-approved pilots
Module 5: Data Strategy for Non-Technical Leaders - The leadership role in data governance and quality
- Understanding data pipelines without technical jargon
- How to ask the right questions about data readiness
- Evaluating internal vs. external data sourcing
- Establishing data ownership and stewardship
- Minimum viable data: What you need to start
- Identifying data silos and integration barriers
- Assessing data bias and fairness at scale
- Building trust in data across departments
- Creating a data strategy communication plan
Module 6: The AI Stakeholder Alignment Protocol - The 6 key stakeholder archetypes in AI projects
- How to speak to legal, compliance, and risk teams confidently
- Tailoring your message for technical versus non-technical audiences
- Running alignment workshops with cross-functional teams
- The 3-part persuasion framework: Problem, Path, Payoff
- Overcoming resistance with psychological safety techniques
- Using pre-mortems to surface concerns early
- Creating shared ownership of AI initiatives
- Building coalition champions across departments
- Measuring stakeholder buy-in progress
Module 7: Designing the Board-Ready AI Proposal - The 5 essential components of every AI strategy document
- Structuring your proposal for executive attention
- How to open with strategic urgency, not technical detail
- Presenting risk mitigation plans that reassure
- Using the SLIDE format: Situation, Leverage, Investment, Delivery, Evidence
- Creating compelling visual summaries for time-poor leaders
- Anticipating and answering the 7 most common board questions
- Aligning with financial planning cycles and budget gates
- Building phased rollout plans with quick wins
- Template: Executive AI strategy proposal (customisable)
Module 8: Risk, Ethics, and Governance in AI Strategy - The 4 ethical red lines in enterprise AI
- Establishing AI governance committees
- Designing for transparency and explainability
- Managing model drift and performance degradation
- Compliance with global AI regulations and frameworks
- Conducting AI impact assessments
- Implementing human-in-the-loop oversight
- Handling data privacy and consent in AI workflows
- Creating AI incident response protocols
- Building public trust in algorithmic decisions
Module 9: The AI Execution Blueprint - The 90-day AI launch sequence
- Assembling the minimum viable team
- Defining success metrics and KPIs
- Setting up feedback loops for early validation
- Running pilot tests with real data and users
- Managing vendor selection and procurement
- Avoiding scope creep in early AI projects
- Documenting decisions and assumptions
- Using rapid iteration to accelerate learning
- Escalating roadblocks using structured escalation paths
Module 10: Measuring and Communicating AI Value - From output to outcome: What really matters in AI ROI
- Quantifying efficiency, revenue, and risk reduction gains
- Creating before-and-after performance snapshots
- Using storytelling to amplify impact
- Reporting progress without technical overcomplication
- Developing internal case studies for broader adoption
- Tracking both leading and lagging indicators
- Updating the board quarterly with confidence
- Adjusting strategy based on real data
- Scaling success: When and how to go enterprise-wide
Module 11: Leading Cross-Functional AI Teams - How to lead without authority in matrix organisations
- Setting psychological safety for AI innovation
- Running effective stand-ups and retrospectives
- Managing conflict between data, tech, and business teams
- Facilitating solution brainstorming sessions
- Delegating AI tasks with clarity and accountability
- Building team trust in ambiguous environments
- Recognising and rewarding contributions publicly
- Managing burnout in high-pressure AI projects
- Developing team AI literacy at all levels
Module 12: Scaling AI Across the Organisation - The 3 phases of AI adoption: pilot, expand, entrench
- Creating an AI centre of excellence
- Developing internal AI champions
- Building reusable templates and playbooks
- Establishing AI project intake and prioritisation
- Integrating AI into existing strategic planning cycles
- Securing sustained funding and resources
- Driving cultural change through visible wins
- Managing resistance at scale
- Measuring organisational AI maturity over time
Module 13: AI Strategy in Regulated and Complex Industries - Tailoring AI strategy for healthcare, finance, and government
- Working within compliance and audit constraints
- Designing for regulator readiness
- Documentation standards for auditable AI
- Handling third-party model risk
- Ensuring algorithmic fairness in high-stakes decisions
- Conducting external validation and peer review
- Navigating procurement rules for AI vendors
- Managing legacy system integration challenges
- Case study: Deploying AI in a Tier 1 bank under Basel III
Module 14: The Leader’s Toolkit: Templates, Checklists, and Workflows - AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
- The AI Opportunity Matrix: Value vs. feasibility scoring
- Using the IDEA filter: Impact, Data, Effort, Alignment
- Identifying low-hanging fruit with high visibility
- Avoiding the “shiny object” trap in AI selection
- How to conduct a 90-minute AI opportunity workshop with your team
- Prioritising use cases by board-level relevance
- Aligning AI initiatives with ESG, compliance, and risk mandates
- Mapping AI to customer journey pain points
- Calculating potential ROI for operational and revenue AI
- Case study: From 47 ideas to 3 board-approved pilots
Module 5: Data Strategy for Non-Technical Leaders - The leadership role in data governance and quality
- Understanding data pipelines without technical jargon
- How to ask the right questions about data readiness
- Evaluating internal vs. external data sourcing
- Establishing data ownership and stewardship
- Minimum viable data: What you need to start
- Identifying data silos and integration barriers
- Assessing data bias and fairness at scale
- Building trust in data across departments
- Creating a data strategy communication plan
Module 6: The AI Stakeholder Alignment Protocol - The 6 key stakeholder archetypes in AI projects
- How to speak to legal, compliance, and risk teams confidently
- Tailoring your message for technical versus non-technical audiences
- Running alignment workshops with cross-functional teams
- The 3-part persuasion framework: Problem, Path, Payoff
- Overcoming resistance with psychological safety techniques
- Using pre-mortems to surface concerns early
- Creating shared ownership of AI initiatives
- Building coalition champions across departments
- Measuring stakeholder buy-in progress
Module 7: Designing the Board-Ready AI Proposal - The 5 essential components of every AI strategy document
- Structuring your proposal for executive attention
- How to open with strategic urgency, not technical detail
- Presenting risk mitigation plans that reassure
- Using the SLIDE format: Situation, Leverage, Investment, Delivery, Evidence
- Creating compelling visual summaries for time-poor leaders
- Anticipating and answering the 7 most common board questions
- Aligning with financial planning cycles and budget gates
- Building phased rollout plans with quick wins
- Template: Executive AI strategy proposal (customisable)
Module 8: Risk, Ethics, and Governance in AI Strategy - The 4 ethical red lines in enterprise AI
- Establishing AI governance committees
- Designing for transparency and explainability
- Managing model drift and performance degradation
- Compliance with global AI regulations and frameworks
- Conducting AI impact assessments
- Implementing human-in-the-loop oversight
- Handling data privacy and consent in AI workflows
- Creating AI incident response protocols
- Building public trust in algorithmic decisions
Module 9: The AI Execution Blueprint - The 90-day AI launch sequence
- Assembling the minimum viable team
- Defining success metrics and KPIs
- Setting up feedback loops for early validation
- Running pilot tests with real data and users
- Managing vendor selection and procurement
- Avoiding scope creep in early AI projects
- Documenting decisions and assumptions
- Using rapid iteration to accelerate learning
- Escalating roadblocks using structured escalation paths
Module 10: Measuring and Communicating AI Value - From output to outcome: What really matters in AI ROI
- Quantifying efficiency, revenue, and risk reduction gains
- Creating before-and-after performance snapshots
- Using storytelling to amplify impact
- Reporting progress without technical overcomplication
- Developing internal case studies for broader adoption
- Tracking both leading and lagging indicators
- Updating the board quarterly with confidence
- Adjusting strategy based on real data
- Scaling success: When and how to go enterprise-wide
Module 11: Leading Cross-Functional AI Teams - How to lead without authority in matrix organisations
- Setting psychological safety for AI innovation
- Running effective stand-ups and retrospectives
- Managing conflict between data, tech, and business teams
- Facilitating solution brainstorming sessions
- Delegating AI tasks with clarity and accountability
- Building team trust in ambiguous environments
- Recognising and rewarding contributions publicly
- Managing burnout in high-pressure AI projects
- Developing team AI literacy at all levels
Module 12: Scaling AI Across the Organisation - The 3 phases of AI adoption: pilot, expand, entrench
- Creating an AI centre of excellence
- Developing internal AI champions
- Building reusable templates and playbooks
- Establishing AI project intake and prioritisation
- Integrating AI into existing strategic planning cycles
- Securing sustained funding and resources
- Driving cultural change through visible wins
- Managing resistance at scale
- Measuring organisational AI maturity over time
Module 13: AI Strategy in Regulated and Complex Industries - Tailoring AI strategy for healthcare, finance, and government
- Working within compliance and audit constraints
- Designing for regulator readiness
- Documentation standards for auditable AI
- Handling third-party model risk
- Ensuring algorithmic fairness in high-stakes decisions
- Conducting external validation and peer review
- Navigating procurement rules for AI vendors
- Managing legacy system integration challenges
- Case study: Deploying AI in a Tier 1 bank under Basel III
Module 14: The Leader’s Toolkit: Templates, Checklists, and Workflows - AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
- The 6 key stakeholder archetypes in AI projects
- How to speak to legal, compliance, and risk teams confidently
- Tailoring your message for technical versus non-technical audiences
- Running alignment workshops with cross-functional teams
- The 3-part persuasion framework: Problem, Path, Payoff
- Overcoming resistance with psychological safety techniques
- Using pre-mortems to surface concerns early
- Creating shared ownership of AI initiatives
- Building coalition champions across departments
- Measuring stakeholder buy-in progress
Module 7: Designing the Board-Ready AI Proposal - The 5 essential components of every AI strategy document
- Structuring your proposal for executive attention
- How to open with strategic urgency, not technical detail
- Presenting risk mitigation plans that reassure
- Using the SLIDE format: Situation, Leverage, Investment, Delivery, Evidence
- Creating compelling visual summaries for time-poor leaders
- Anticipating and answering the 7 most common board questions
- Aligning with financial planning cycles and budget gates
- Building phased rollout plans with quick wins
- Template: Executive AI strategy proposal (customisable)
Module 8: Risk, Ethics, and Governance in AI Strategy - The 4 ethical red lines in enterprise AI
- Establishing AI governance committees
- Designing for transparency and explainability
- Managing model drift and performance degradation
- Compliance with global AI regulations and frameworks
- Conducting AI impact assessments
- Implementing human-in-the-loop oversight
- Handling data privacy and consent in AI workflows
- Creating AI incident response protocols
- Building public trust in algorithmic decisions
Module 9: The AI Execution Blueprint - The 90-day AI launch sequence
- Assembling the minimum viable team
- Defining success metrics and KPIs
- Setting up feedback loops for early validation
- Running pilot tests with real data and users
- Managing vendor selection and procurement
- Avoiding scope creep in early AI projects
- Documenting decisions and assumptions
- Using rapid iteration to accelerate learning
- Escalating roadblocks using structured escalation paths
Module 10: Measuring and Communicating AI Value - From output to outcome: What really matters in AI ROI
- Quantifying efficiency, revenue, and risk reduction gains
- Creating before-and-after performance snapshots
- Using storytelling to amplify impact
- Reporting progress without technical overcomplication
- Developing internal case studies for broader adoption
- Tracking both leading and lagging indicators
- Updating the board quarterly with confidence
- Adjusting strategy based on real data
- Scaling success: When and how to go enterprise-wide
Module 11: Leading Cross-Functional AI Teams - How to lead without authority in matrix organisations
- Setting psychological safety for AI innovation
- Running effective stand-ups and retrospectives
- Managing conflict between data, tech, and business teams
- Facilitating solution brainstorming sessions
- Delegating AI tasks with clarity and accountability
- Building team trust in ambiguous environments
- Recognising and rewarding contributions publicly
- Managing burnout in high-pressure AI projects
- Developing team AI literacy at all levels
Module 12: Scaling AI Across the Organisation - The 3 phases of AI adoption: pilot, expand, entrench
- Creating an AI centre of excellence
- Developing internal AI champions
- Building reusable templates and playbooks
- Establishing AI project intake and prioritisation
- Integrating AI into existing strategic planning cycles
- Securing sustained funding and resources
- Driving cultural change through visible wins
- Managing resistance at scale
- Measuring organisational AI maturity over time
Module 13: AI Strategy in Regulated and Complex Industries - Tailoring AI strategy for healthcare, finance, and government
- Working within compliance and audit constraints
- Designing for regulator readiness
- Documentation standards for auditable AI
- Handling third-party model risk
- Ensuring algorithmic fairness in high-stakes decisions
- Conducting external validation and peer review
- Navigating procurement rules for AI vendors
- Managing legacy system integration challenges
- Case study: Deploying AI in a Tier 1 bank under Basel III
Module 14: The Leader’s Toolkit: Templates, Checklists, and Workflows - AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
- The 4 ethical red lines in enterprise AI
- Establishing AI governance committees
- Designing for transparency and explainability
- Managing model drift and performance degradation
- Compliance with global AI regulations and frameworks
- Conducting AI impact assessments
- Implementing human-in-the-loop oversight
- Handling data privacy and consent in AI workflows
- Creating AI incident response protocols
- Building public trust in algorithmic decisions
Module 9: The AI Execution Blueprint - The 90-day AI launch sequence
- Assembling the minimum viable team
- Defining success metrics and KPIs
- Setting up feedback loops for early validation
- Running pilot tests with real data and users
- Managing vendor selection and procurement
- Avoiding scope creep in early AI projects
- Documenting decisions and assumptions
- Using rapid iteration to accelerate learning
- Escalating roadblocks using structured escalation paths
Module 10: Measuring and Communicating AI Value - From output to outcome: What really matters in AI ROI
- Quantifying efficiency, revenue, and risk reduction gains
- Creating before-and-after performance snapshots
- Using storytelling to amplify impact
- Reporting progress without technical overcomplication
- Developing internal case studies for broader adoption
- Tracking both leading and lagging indicators
- Updating the board quarterly with confidence
- Adjusting strategy based on real data
- Scaling success: When and how to go enterprise-wide
Module 11: Leading Cross-Functional AI Teams - How to lead without authority in matrix organisations
- Setting psychological safety for AI innovation
- Running effective stand-ups and retrospectives
- Managing conflict between data, tech, and business teams
- Facilitating solution brainstorming sessions
- Delegating AI tasks with clarity and accountability
- Building team trust in ambiguous environments
- Recognising and rewarding contributions publicly
- Managing burnout in high-pressure AI projects
- Developing team AI literacy at all levels
Module 12: Scaling AI Across the Organisation - The 3 phases of AI adoption: pilot, expand, entrench
- Creating an AI centre of excellence
- Developing internal AI champions
- Building reusable templates and playbooks
- Establishing AI project intake and prioritisation
- Integrating AI into existing strategic planning cycles
- Securing sustained funding and resources
- Driving cultural change through visible wins
- Managing resistance at scale
- Measuring organisational AI maturity over time
Module 13: AI Strategy in Regulated and Complex Industries - Tailoring AI strategy for healthcare, finance, and government
- Working within compliance and audit constraints
- Designing for regulator readiness
- Documentation standards for auditable AI
- Handling third-party model risk
- Ensuring algorithmic fairness in high-stakes decisions
- Conducting external validation and peer review
- Navigating procurement rules for AI vendors
- Managing legacy system integration challenges
- Case study: Deploying AI in a Tier 1 bank under Basel III
Module 14: The Leader’s Toolkit: Templates, Checklists, and Workflows - AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
- From output to outcome: What really matters in AI ROI
- Quantifying efficiency, revenue, and risk reduction gains
- Creating before-and-after performance snapshots
- Using storytelling to amplify impact
- Reporting progress without technical overcomplication
- Developing internal case studies for broader adoption
- Tracking both leading and lagging indicators
- Updating the board quarterly with confidence
- Adjusting strategy based on real data
- Scaling success: When and how to go enterprise-wide
Module 11: Leading Cross-Functional AI Teams - How to lead without authority in matrix organisations
- Setting psychological safety for AI innovation
- Running effective stand-ups and retrospectives
- Managing conflict between data, tech, and business teams
- Facilitating solution brainstorming sessions
- Delegating AI tasks with clarity and accountability
- Building team trust in ambiguous environments
- Recognising and rewarding contributions publicly
- Managing burnout in high-pressure AI projects
- Developing team AI literacy at all levels
Module 12: Scaling AI Across the Organisation - The 3 phases of AI adoption: pilot, expand, entrench
- Creating an AI centre of excellence
- Developing internal AI champions
- Building reusable templates and playbooks
- Establishing AI project intake and prioritisation
- Integrating AI into existing strategic planning cycles
- Securing sustained funding and resources
- Driving cultural change through visible wins
- Managing resistance at scale
- Measuring organisational AI maturity over time
Module 13: AI Strategy in Regulated and Complex Industries - Tailoring AI strategy for healthcare, finance, and government
- Working within compliance and audit constraints
- Designing for regulator readiness
- Documentation standards for auditable AI
- Handling third-party model risk
- Ensuring algorithmic fairness in high-stakes decisions
- Conducting external validation and peer review
- Navigating procurement rules for AI vendors
- Managing legacy system integration challenges
- Case study: Deploying AI in a Tier 1 bank under Basel III
Module 14: The Leader’s Toolkit: Templates, Checklists, and Workflows - AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
- The 3 phases of AI adoption: pilot, expand, entrench
- Creating an AI centre of excellence
- Developing internal AI champions
- Building reusable templates and playbooks
- Establishing AI project intake and prioritisation
- Integrating AI into existing strategic planning cycles
- Securing sustained funding and resources
- Driving cultural change through visible wins
- Managing resistance at scale
- Measuring organisational AI maturity over time
Module 13: AI Strategy in Regulated and Complex Industries - Tailoring AI strategy for healthcare, finance, and government
- Working within compliance and audit constraints
- Designing for regulator readiness
- Documentation standards for auditable AI
- Handling third-party model risk
- Ensuring algorithmic fairness in high-stakes decisions
- Conducting external validation and peer review
- Navigating procurement rules for AI vendors
- Managing legacy system integration challenges
- Case study: Deploying AI in a Tier 1 bank under Basel III
Module 14: The Leader’s Toolkit: Templates, Checklists, and Workflows - AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
- AI Opportunity Assessment Matrix (downloadable)
- Stakeholder Alignment Map (customisable)
- AI Ethics Checklist for Executives
- Board-Ready Strategy Proposal Template
- Pilot Project Launch Planner
- Risk Register for AI Initiatives
- 90-Day Execution Calendar
- AI Communication Playbook for Change Management
- ROI Calculator for AI Projects
- Monthly AI Progress Dashboard (Excel and Google Sheets)
Module 15: Building Your Personal AI Leadership Brand - Positioning yourself as the go-to AI strategist
- Developing your executive narrative for AI
- Presenting at leadership forums and industry events
- Writing internal thought leadership pieces
- Using LinkedIn and professional networks strategically
- Creating a personal portfolio of AI wins
- Seeking stretch assignments in digital transformation
- Mentoring others to amplify your influence
- Navigating promotion conversations with confidence
- Planning your next career move with AI credibility
Module 16: Certification, Next Steps, and Lifelong Advancement - How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead
- How to prepare for the final assessment
- Submitting your board-ready AI strategy project
- Receiving feedback and finalising your deliverable
- Earning your Certificate of Completion from The Art of Service
- Adding your certification to LinkedIn and CV
- Accessing alumni resources and updates
- Joining the network of AI-driven leaders
- Exclusive invitations to strategy roundtables
- Continuing your journey: Advanced leadership pathways
- The next 12 months of AI strategy - and how to stay ahead