AI, Business and the Future of Work Training Course – London, 1–5 Feb 2027

AI, Business and the Future of Work is a 1-week training course for business leaders, HR directors, transformation managers and team leaders that ends with a human-AI workforce roadmap for one business unit. Generative and predictive AI now changes which tasks people perform, how roles are graded and which skills an organisation must grow or buy. Jupiter Prime Training offers this AI, Business and the Future of Work course to leaders shaping that shift.

Why AI, Business and the Future of Work Matters Now

Three pressures shape AI, business and the future of work: assistants and agents that absorb routine knowledge tasks, employees who want clarity on how their jobs will change, and customers whose expectations reset business models in retail, banking and professional services. An organisation that redesigns roles deliberately can redeploy talent into higher-judgement work and retain trust; one that automates task by task without a workforce view risks skills gaps, attrition and morale loss. The course draws on ISO/IEC 42001 for responsible AI management and the NIST AI Risk Management Framework (NIST AI RMF) for weighing impacts on people.

Who Gains Most from AI, Business and the Future of Work

• Leaders who decide how products, channels and revenue models change as AI enters the market
• People leaders responsible for job architecture, grading, reward and strategic workforce planning
• Transformation owners who sequence automation initiatives and track their effect on capacity
• Line leaders who reorganise daily routines when assistants take over parts of a role
• Learning leads who define reskilling pathways and capability frameworks

A leadership group that brings business, HR and transformation members together gains most, because job redesign decisions cut across all three functions.

AI, Business and the Future of Work Capabilities

Participants turn broad talk about jobs and machines into task-level evidence, role options and a sequenced workforce response.

• Assess task automation and augmentation exposure across roles — workforce planning decisions
• Weigh business model shifts created by AI against current revenue streams — executive committees
• Design redesigned roles that combine human judgement with AI assistants — HR and line leaders
• Calculate reskilling, redeployment and hiring options for affected job families — finance and HR partners
• Apply responsible AI checks to workforce decisions — employee representatives and risk owners
• Communicate the case for change and new career paths — employees and works councils

Key AI, Business and the Future of Work Terms

• Task-based analysis — breaking each role into tasks to judge which ones AI can automate, augment or leave unchanged.
• Augmentation — using AI to raise the speed or quality of human work rather than replace the worker.
• Job architecture — the structure of job families, levels and grades that defines roles across an organisation.
• Reskilling — training employees in new skills so they can move into different roles as tasks change.
• Strategic workforce planning — forecasting the skills and headcount a business will need and closing the gap over time.
• Human-in-the-loop — a design where a person reviews or approves AI outputs before they take effect.

AI, Business and the Future of Work Day by Day

Day 1: How AI Reshapes Markets and Business Models

• AI Value Chain Mapping — Where Margins and Customer Relationships Shift
• Platform and Subscription Model Shifts — Revenue Exposure in Core Products
• Generative AI Assistants and Agents — New Ways of Serving Customers
• Competitor Scenario Grid — Timing of Business Model Responses
• Sector Contrasts in Banking and Retail — Lessons for Other Industries

Day 2: Task-Level Analysis of Jobs

• Role-to-Task Decomposition — Building an Evidence Base for Redesign
• Automation and Augmentation Exposure Scoring — Prioritising Job Families
• Skills Taxonomy Mapping — Declining, Stable and Emerging Skills
• Productivity Release Estimation — Capacity Freed for Higher-Value Tasks
• Employee Listening Methods — Capturing Concerns About Changing Roles

Day 3: Redesigning Roles and Organisation Structures

• Human-AI Role Blueprints — Dividing Judgement and Execution
• Job Architecture and Grading Updates — Fair Recognition of Changed Roles
• Span of Control and Layer Review — Flatter Structures With Assistants
• Human-in-the-Loop Checkpoints — Accountability for AI-Supported Decisions
• ISO/IEC 42001 and NIST AI RMF Impact Checks — Effects on Employees

Day 4: Reskilling, Redeployment and Change

• Build, Buy, Borrow, Redeploy Options — Closing Skills Gaps
• Reskilling Pathway Design — From Declining Roles to Growth Roles
• Strategic Workforce Planning Model — Headcount and Cost Trajectories
• Change Narrative and Career Messaging — Retaining Trust During Transition
• Workforce Metrics Dashboard — Tracking Adoption, Mobility and Attrition

Day 5: Practising the Human-AI Workforce Roadmap

• Exposure Scores From Day 2 — Selecting Priority Job Families
• Role Blueprints From Day 3 — Target Organisation for One Unit
• Reskilling and Redeployment Options From Day 4 — Costed Choices
• Stakeholder Briefing Pack — Executive, HR and Employee Audiences
• Human-AI Workforce Roadmap — Sequenced Changes for One Business Unit

Applying AI, Business and the Future of Work After the Course

• Run a task decomposition session for one job family, such as customer service agents or finance analysts, and score each task for automation and augmentation exposure.
• Draft a reskilling pathway for one declining role, linking target skills, learning steps and the growth role it leads into.

AI, Business and the Future of Work Questions (FAQ)

What is AI, business and the future of work and why does it matter now?

AI, business and the future of work is the study of how AI changes business models, tasks, roles and skills. It matters now because assistants already handle routine knowledge tasks, and leaders must decide how to redesign jobs before change happens to them.

Which roles gain most from AI, business and the future of work training?

Business leaders, HR directors, transformation managers and team leaders gain most. Each owns part of the response, from revenue models and job grading to reskilling budgets and the daily routines of teams.

How does AI, business and the future of work differ from an AI strategy course?

It centres on people, roles and organisation design rather than technology choices or use-case portfolios. You analyse tasks, redesign jobs and plan reskilling, while an AI strategy course focuses on selecting and funding AI initiatives.

What do you bring back from AI, business and the future of work training?

You bring back a human-AI workforce roadmap for one business unit. It sets priority job families, redesigned roles, reskilling and redeployment choices, and a briefing approach for executives and employees.

AI, Business and the Future of Work: The Way Forward

The human-AI workforce roadmap informs the first people decision: which job family to redesign before the next automation wave. Business leaders, HR partners and line managers use it to align budgets and messages. After the first redesign, revisit the exposure scores and employee listening results, since real usage of assistants often shifts which tasks people keep.