AI for SMEs: Plan, Pilot & Scale with the 5P Model

Welcome to the first stage of the 5P Framework — Prepare. In this section, we focus on laying the right foundation for successful AI adoption. You'll learn why preparation is more than just planning — it’s about building leadership alignment, developing team literacy, and assessing your organisational readiness. This page sets the tone for the modules ahead and introduces the mindset required to adopt AI in a way that’s strategic, inclusive, and sustainable.

This module provides a high-level explainer of what the Prepare phase involves. You'll get a preview of the key areas we’ll cover — including leadership, culture, governance, team structure, and self-assessment tools. If you’re wondering where to start your AI journey, this video will make it clear why this phase comes first and how to move forward with confidence.

AI success starts at the top. This lesson explores the critical role leaders play in shaping how AI is adopted across the business. From setting the vision and allocating resources to reducing fear and modelling curiosity — leadership behaviour drives culture. Learn what it looks like when AI is led with clarity, and why your engagement matters more than any single tool.

Use this practical checklist to make leadership visible and credible during AI adoption. Actions include sponsoring a micro-pilot, approving risk frameworks, attending training, and communicating the "why" behind AI initiatives. It’s a tool to inspire clarity and consistency.

AI is not just a tech project — it’s a cross-functional business transformation. This page walks you through how to form a dedicated AI workgroup to drive alignment, reduce silos, and create shared ownership. You’ll learn who to involve, how to define the group’s mission, and how this simple structure can accelerate adoption across your company.

Before jumping into tools or pilots, it’s important to understand where your organisation stands today. This module introduces the AI Readiness Self-Assessment — a structured tool that evaluates your current strengths and gaps across five dimensions: Strategy, Governance, People, Data, and Technology. This isn’t just about scoring — it’s about getting honest insight into what’s working, what’s missing, and what to focus on next.

Now that you’ve seen the assessment criteria, this page explains how to actually use the tool. You’ll learn how to rate your organisation across each dimension and how your total score maps to a maturity level — from Not Ready to Strategically Ready. We also highlight “must-score” questions that act as readiness blockers, ensuring your score reflects not just activity, but quality and alignment.

It’s not enough for leadership to be aligned — your people need the capability and confidence to work with AI, too. This module introduces the AI Literacy Self-Assessment, which helps you evaluate your team’s understanding of key concepts, tools, risks, and role-specific use cases. It’s an essential tool to identify training needs and create safe, informed usage across departments.

This lesson shows you how to use the AI Literacy Self-Assessment to determine your team's current fluency. You’ll assess five areas, including foundational awareness, prompt fluency, critical thinking, role-based usage, and culture of learning. The tool will also help you understand the right next step — whether it's foundational training, role-specific enablement, or scaling internal champions.

AI adoption isn’t a one-time event — it’s an ongoing capability. This module outlines how to build a culture of continuous learning that supports sustainable AI integration. You’ll explore different formats like live training, micro-quizzes, badges, and department-specific learning pathways that help teams retain knowledge, experiment safely, and stay up to speed as tools evolve.

See how one online retailer improved conversion rates by 12% and reduced support workload using a simple AI chatbot. This real-world case study showcases how even small AI pilots can drive measurable outcomes in customer experience and revenue.

You’ve completed your readiness and literacy assessments — now what? This session gives you specific actions to take, like forming an AI workgroup, choosing a first pilot, and aligning leadership on goals.

Ready to take the next step in your AI journey? If you’re looking to build confidence, capability, and alignment across your team, we can help. Better People offers AI fluency training designed specifically for SMEs which can be tailored to your team’s roles, challenges, and current level of knowledge. Whether you’re just starting out or looking to accelerate adoption, we’ll meet you where you are.

This module marks the second stage in the 5P Framework — Pilot. After preparing your team and aligning your organisation, it's time to start testing AI in the real world. This section introduces the concept of running structured, low-risk AI pilot projects to explore what's possible, prove value, and build momentum. Whether you're experimenting with tools like ChatGPT or testing automation platforms in your workflows, this is where curiosity turns into action.

In this video, we break down exactly what the Pilot phase is all about. You’ll learn how pilots serve as the “test and learn” zone of AI adoption — allowing you to explore opportunities without major disruption. We’ll walk through different types of pilots, how to scope them, and how they fit into your broader AI strategy. This explainer sets the foundation for all the hands-on activities that follow.

There are three core types of AI pilot projects, and each serves a unique purpose. This page introduces the three categories: Playgrounds, Pressure Points, and Blue Ocean projects. You’ll learn why a balanced approach across these types helps you build internal confidence, unlock quick wins, and explore innovative use cases — all while keeping risk low and learning high.

Playgrounds are small, low-risk experiments designed to build confidence and spark curiosity. This section dives deeper into how Playgrounds work and why they’re so powerful for teams just starting out. You’ll explore real-world examples — like using AI to summarise emails or draft social posts — and learn how Playgrounds help shift team culture from hesitation to exploration.

Blue Ocean pilots are all about innovation. Instead of focusing on efficiency, these projects explore how AI can create brand-new ways of delivering value. From building multilingual training videos to developing AI-powered customer tools, this section will inspire bold thinking while also offering guardrails to ensure smart scaling and ethical use.

This section introduces Pressure Points — pilot projects focused on tasks that are repetitive, frustrating, or costly. These are often the quickest path to measurable ROI. You’ll learn how to identify bottlenecks in your business where AI can relieve pain, save time, and drive efficiency. Because these pilots often involve sensitive data or core operations, this module also introduces the importance of governance and ethical considerations from the start.

Before you automate anything, you need to know where the real problems lie. This page gives you a simple process to identify and prioritise the biggest pain points in your business — by asking the right questions and involving your team. You’ll learn how to evaluate opportunities based on impact, frequency, and potential ROI so you can choose the right projects to test first.

In this module, we guide you through a step-by-step process for uncovering hidden friction in your workflows. From staff interviews to real-time observations and data analysis, you’ll learn how to combine qualitative and quantitative signals to uncover the best AI pilot opportunities. It’s not just about tech — it’s about understanding your people, your processes, and where change will matter most.

Need inspiration? This page introduces part of the AI Use Case Library, with practical, role-specific examples across Sales, Marketing, and Customer Support. Whether it’s lead scoring, content creation, or support automation — you’ll see what’s already working in real businesses and start identifying where AI could apply to yours.

This worksheet helps you turn scattered ideas into structured pilot opportunities. It guides you through identifying tasks, pain points, and signals that suggest AI could add value — whether through automation, optimisation, or innovation. You’ll also capture key details like required data, desired outcomes, and tool options. Use this as a practical first step to align your team, prioritise where to start, and ensure every AI idea connects to a real business need.

Not all ideas should be tackled at once. This module teaches you how to prioritise your list of potential use cases using a simple 2x2 matrix: High vs Low Impact and Easy vs Hard to Execute. This framework helps you choose quick wins to pilot now, while setting aside more complex ideas for later.

With thousands of AI tools on the market, choosing the right one can be overwhelming — and costly if you get it wrong. This scorecard gives you a structured, no-nonsense way to evaluate tools based on what actually matters for SMEs: ease of use, data privacy, pricing, integration, and business fit. You'll score each tool across ten criteria and set minimum thresholds to avoid wasting time or budget. Whether you're running a pilot or scaling up, this framework helps you find tools your team will actually use — safely, quickly, and confidently.

Before you launch any AI pilot, you need to define what success actually looks like. This template helps you do exactly that — by focusing not on the AI itself, but on the business outcomes it’s meant to improve. You’ll set clear, measurable criteria tied to goals like time saved, quality maintained, team adoption, risk management, and reusability. This ensures your pilot isn’t just an experiment — it’s a meaningful test with a real business case behind it.

Great pilots don’t happen by accident — they’re designed with intention. This template gives you a simple structure to scope and plan your AI pilot before you hit “go.” You’ll define the problem, set clear goals, choose the right team and tools, and outline your timeline, risks, and success metrics. It’s everything you need to make your AI experiment focused, manageable, and aligned with your business objectives.

Once your AI pilot is up and running, it's important to stay organised and track what’s happening. This worksheet helps you capture all the essential details — from objectives and timelines to tools used and departments involved. It’s a simple way to keep your pilot visible, accountable, and easy to report on. Use it to stay aligned, share updates with stakeholders, and build a repeatable process for future pilots.

A successful pilot isn’t just about results — it’s about what you learn along the way. This template helps you capture feedback, document lessons, and reflect on what worked, what didn’t, and what should change next time. It encourages teams to share their experience, identify improvements, and decide whether a pilot should be expanded or adjusted. Use this to turn every pilot into a stepping stone for smarter, more scalable AI adoption.

Now that you’ve explored how to design, run, and evaluate an AI pilot, it’s time to take action. This slide prompts you to identify your top three next steps — whether that’s choosing a use case, booking a training session, or kicking off your first experiment. The goal is to move from planning to progress. Small, focused actions taken now will build the momentum you need to drive AI adoption forward in your business.

Welcome to the fourth stage of the 5P Framework — Promote. This phase is all about making AI sustainable and scalable in your organisation. You’ll explore how to communicate success, build buy-in across teams, and formalise the tools, policies, and processes needed to support long-term adoption. This module is where pilots become playbooks, and one-off wins become repeatable systems.

In this video, we break down what the Promote phase is all about. You’ll learn how to move beyond isolated pilots and start embedding AI into your culture, workflows, and decision-making processes. This explainer introduces the practical tools and templates you'll use — including ROI cheat sheets, business case templates, and internal enablement strategies.

This template helps you build a compelling case for scaling an AI solution across your business. It captures key pilot results, projected impact, costs, and risks — all in one page. Use it to present clear, evidence-based recommendations to decision-makers and ensure your AI projects are aligned with business goals and resource planning.

Before you scale any AI solution, it’s essential to understand the return on investment. This slide introduces a cheat sheet to help you quickly estimate ROI using metrics like time saved, cost reductions, productivity gains, and employee feedback. It’s a practical way to show the value of your pilot — without needing a finance degree.

In this case study, see how a mid-sized marketing agency used AI to dramatically reduce the time spent creating client proposals. By adopting document automation tools, they cut proposal creation time by 75%, increased capacity by 30%, and improved their win rate — all without adding new headcount. It’s a powerful example of how AI can deliver measurable impact in high-value, time-intensive tasks.

You’ve now reached the point where AI pilots turn into business momentum. This slide helps you identify the next three actions to take to promote AI successfully across your organisation — whether that’s building a business case, running a team showcase, or booking additional training. The goal here is to take what worked and make it stick, sustainably and at scale.

This video overview outlines what you’ll be working through in the Plan phase. It introduces the key goals of this stage, the common challenges businesses face when scaling AI, and the specific tools you’ll use to move forward — from policy templates to training pathways. The explainer also reinforces the importance of moving thoughtfully, not reactively, so you avoid risk and build sustainable momentum.

This slide explores the critical role that high-quality data plays in the success of any AI initiative. You’ll learn why poor data — whether incomplete, inconsistent, or siloed — is often the reason AI projects underdeliver. It introduces key data quality dimensions and helps you begin to assess whether your organisation’s data is ready to support scaled adoption.

This slide explores the critical role that high-quality data plays in the success of any AI initiative. You’ll learn why poor data — whether incomplete, inconsistent, or siloed — is often the reason AI projects underdeliver. It introduces key data quality dimensions and helps you begin to assess whether your organisation’s data is ready to support scaled adoption.

This slide introduces a simple audit tool that lets you quickly assess the health of your data using six key criteria: accuracy, completeness, consistency, relevance, accessibility, and security. It’s designed to be fast, practical, and approachable — so you can start identifying red flags in your current datasets before pushing them into AI workflows.

Here you’ll go one step deeper into assessing your data readiness. This guide helps you define what “good data” looks like in your context, spot gaps in data coverage or quality, and understand what might need to be cleaned, structured, or secured before scaling your AI use cases.

An AI Use Policy helps set clear boundaries and expectations for how AI tools should (and shouldn’t) be used across your organisation. It protects your business from misuse, ensures compliance with data and privacy standards, and builds trust among your team. This slide guides you through the key elements to include — from approved tools and acceptable use, to human oversight and risk mitigation — so your adoption of AI is responsible, safe, and aligned with your values.

Effective communication is a key enabler of successful AI adoption. This slide presents five core communication principles to help you explain AI projects clearly, reduce fear or resistance, and build trust across the organisation. It supports internal alignment and helps ensure AI isn’t seen as a top-down initiative, but something your teams feel part of.

This slide gives you concrete examples of what good internal communication looks like at different stages of AI adoption — from early pilots to post-rollout support. These sample messages make it easier for you to share updates, set expectations, and keep teams informed in plain, practical language.

As AI use expands, data privacy becomes a much bigger concern. This slide introduces a checklist to help you review how sensitive data is stored, accessed, and used. You’ll be able to flag risks, close compliance gaps, and ensure you’re not unknowingly exposing personal or confidential data through AI use.

AI training should never be one-size-fits-all. This slide introduces a structured approach to mapping out different training needs across your organisation — from frontline staff to senior leaders. It ensures each role gets the right level of fluency, helping build confidence, reduce risk, and support wide-scale adoption.

In this case study, you’ll see how a business used solid planning and strong data foundations to scale a successful pilot focused on inventory forecasting. The story highlights how the tools in the Plan phase come together in practice — reducing waste, improving accuracy, and creating measurable business impact.

We introduce the final phase of the 5P AI Adoption Framework: Prosper. At this stage, the focus is on embedding AI into your business’s DNA. That means scaling what worked, assigning clear ownership, integrating tools into core workflows, and supporting teams through training and enablement. An AI-first strategy isn’t just about adopting technology — it’s about making AI part of how the business thinks, operates, and grows.

This explainer outlines the four core levers of the Prosper phase: roll out successful pilots, integrate AI into core workflows, assign ownership across departments, and provide the support needed for adoption to scale. It sets the tone for what it means to move from experimentation to real transformation.

We offer a powerful mindset reminder: without a clear AI strategy, businesses risk chasing too many disconnected tools and use cases. The result? Fragmentation, wasted resources, and low impact. This is a call to pause, prioritise, and move forward with a focused, intentional approach to AI adoption.

This slide focuses on moving from experiments to execution. You’ll identify successful pilots worth scaling, assign clear ownership by business unit, and support rollout with training and documentation. This is where AI transitions from a test case to a supported solution embedded in real workflows.

This slide introduces both a 90-day tactical roadmap and a 12-month strategic roadmap. You’ll map your next steps across initiatives, owners, and outcomes — creating alignment and visibility across teams. The roadmap keeps your adoption structured, measurable, and scalable.

AI adoption only succeeds when people are equipped to use it. This slide outlines a four-part approach to capability-building: tailored role-based pathways, AI Champions, prompt libraries and playbooks, and continuous learning refreshes. It shows how to move AI from early adopters to the entire organisation.

We highlight the hidden risks that surface when scaling AI: cost creep, vendor lock-in, and poor integration. It shows you how to anticipate and avoid these issues through structured planning, tool evaluation, and integration strategies that keep your tech stack sustainable.

Here, you’re given a practical framework to evaluate AI tools holistically. This slide introduces five cost categories: upfront, integration, ongoing, hidden, and exit costs. It ensures you account for the real costs of scaling — not just the sticker price — before investing further.

We introduce a quarterly cycle that helps you track success, refine what’s not working, and scale what is. The process includes measuring adoption and impact, gathering feedback, making adjustments, and expanding strong use cases — turning AI into a continuous performance engine.

This slide introduces a practical meeting structure for running quarterly AI reviews. You’ll track adoption, collect team feedback, identify areas to refine, and decide what to scale. It’s designed to help you manage AI adoption like a business function — not a side project.

The Strategy Canvas is your one-page blueprint for aligning AI initiatives with business goals. It captures your vision, top use cases, enablers, risks, and metrics — along with ownership. This tool helps keep everyone aligned and ensures AI isn’t just a tech project but a strategic enabler.

We ask you to identify your top three next steps. Whether it’s launching a training program, assigning ownership, or scaling a successful pilot, this is where you commit to forward motion. It also invites you to reach out to Better People for hands-on support in training and enablement.

This slide introduces the final section of the course — a forward-looking view on where AI is headed. You’ll explore emerging trends that are shaping how businesses adopt and scale AI, and understand why staying adaptable is key to long-term success.

Discover the most relevant trends shaping the future of AI — from agentic automation and multi-modal models to embedded AI and evolving regulations. This slide sets the scene for what’s coming next and how to prepare.

Learn about agentic AI — systems that don’t just respond to commands, but actively plan, act, and execute tasks on your behalf. This slide explores how autonomous AI agents are changing workflow automation and decision-making.

This slide introduces a powerful mindset shift: treating AI as a digital team member. You’ll learn how always-on AI can support your team by handling repeatable, time-consuming tasks, day or night.