AI & Business Transformation
Move beyond experimenting with AI tools. Learn to identify valuable opportunities, build practical solutions, and guide their adoption across an organisation.
Connect business needs with AI workflows, internal applications, and intelligent assistants—with security, governance, and measurable impact built into the process.
Overview
An AI prototype is a beginning—not a complete implementation.
What problem does it solve? What information can it access? When should a person intervene? How will the organisation know whether it is working?
This programme teaches you to connect those questions.
Learn to move from business diagnosis to solution design, from a working prototype to testing and governance, and from technical possibility to adoption by the people who will use it.
01.
Understand processes, identify bottlenecks, and prioritise use cases with a clear business rationale.
02.
Create AI-enabled applications, automations, and assistants around a defined need.
03.
Address data handling, access controls, testing, and human oversight from the outset.
04.
Present the solution, estimate its value, and define how progress will be measured.
Who it is for
Turn process knowledge and stakeholder needs into actionable AI implementation plans.
Explore how AI and automation can address repetitive work, process bottlenecks, and service handoffs.
Connect AI-enabled tools with organisational systems, security requirements, and operational practices.
Build a practical framework for prioritising initiatives, evaluating solutions, and guiding adoption.
Develop a structured approach to AI discovery, solution design, prototyping, and executive communication.
Build on your existing experience while developing a new set of implementation skills.
No prior coding background is required.
The programme introduces AI-assisted building and automation alongside the architecture, security, and business judgement needed to use them purposefully.
Learning outcomes
Know where AI belongs, how to implement it and how to evaluate the result.
01.
Turn process knowledge and stakeholder needs into actionable AI implementation plans.
02.
Translate business challenges into implementation briefs, solution architecture and informed build-versus-buy decisions.
03.
Create internal applications and automated workflows using the tools covered in the programme.
04.
Prototype knowledge assistants and agent-based workflows around defined business needs.
05.
Define safeguards, test outputs, document limitations and plan governance, monitoring and rollout.
06.
Present a business case supported by an ROI model and measurable KPIs.
Curriculum
08 MODULES / FROM DIAGNOSIS TO IMPLEMENTATION
Understand the practical business implications of large language models, embeddings, and retrieval-augmented generation—the approach used to connect AI responses with a selected knowledge source. Explore process modelling, data flows, architecture patterns, structured prompting, and build-versus-buy decisions.
Practical work:
Create an architecture diagram, AI workflow and implementation canvas.
Project showcase
01 / PROJECT STAGE
Identify the department, map the current process, estimate its time or cost, and define what success would look like after 90 days.
02 / PROJECT STAGE
Show how information moves through the solution. Explain your tool choices, likely failure modes, and escalation paths.
03 / PROJECT STAGE
Create a working workflow with connected components, edge-case handling, and setup documentation.
04 / PROJECT STAGE
Evaluate normal use and challenging inputs. Record known limitations rather than hiding them.
05 / PROJECT STAGE
Document data classification, access controls, personal-data handling, and situations requiring human intervention.
06 / PROJECT STAGE
Develop an ROI model, measurable KPIs, and an executive presentation with a live demonstration.
You finish with more than a demo: a documented implementation project that shows how you think, build, evaluate, and communicate.
Learning experience
The programme combines live instruction and guided practice with independent project development.
Alongside implementation skills, practise problem-solving, teamwork, critical thinking, adaptability, and clear communication.
01
Explore the concepts behind enterprise AI and see how they apply to business decisions.
02
Investigate a process, clarify the need, and challenge assumptions.
03
Translate the brief into an application, automation, or assistant.
04
Test performance, examine risks, and refine the solution.
05
Explain the architecture, limitations, and business case to technical and non-technical stakeholders.
Details
Admissions will provide the timetable and clarify how academic hours are scheduled.
Boötes Academy
BUILD ON WHAT YOU KNOW.
You do not have to leave your existing experience behind to develop a new direction.
Your understanding of customers, teams, processes, or business operations can become the starting point for learning how to implement AI.
At Boötes Academy, this programme connects technical capability with business judgement and the ability to guide change.
Learn to contribute across the conversation—from the people defining the problem to the people building and using the solution.
Career relevance
01
Bring a more structured approach to AI opportunities within your team or organisation.
02
Build a repeatable process for discovery, prioritisation, solution development, and implementation planning.
03
Use your project work to demonstrate how you translate business needs into tested, documented solutions.
AI implementation brings together responsibilities that are often discussed separately:
business analysis, solution design, prototyping, security, governance, and adoption.
Contact
Tell us about your background and what you want to achieve. We’ll share the programme details and help you assess the fit.