📘 Guide

AI Solution Selection Guide

A practical framework for choosing the right AI solutions for your organisation. Understand when to use ChatGPT vs Claude vs private models, build vs buy decisions, and critical selection criteria.

Introduction

Selecting the right AI solution is one of the most consequential decisions your organisation will make. Choose well, and you accelerate innovation while managing risk. Choose poorly, and you face security breaches, compliance violations, wasted investment, or vendor lock-in.

This guide provides a practical framework for AI solution selection, helping you navigate complex decisions about providers, deployment models, integration strategies, and total cost of ownership.

Who This Guide Is For

This guide is designed for:

  • CIOs and CTOs leading AI strategy and technology decisions
  • IT Directors and Architects evaluating solutions and designing AI infrastructure
  • Procurement and Legal teams assessing vendors and contracts
  • Business leaders sponsoring AI initiatives and making investment decisions

The Challenge

The AI solution landscape is complex and rapidly evolving:

  • Provider choices: ChatGPT, Claude, DeepSeek, Gemini, open-source models, or industry-specific solutions?
  • Deployment models: Public cloud APIs, private deployment, on-premise, or hybrid?
  • Integration strategies: Standalone tools, embedded AI in enterprise platforms (Salesforce Einstein, SAP Joule, Microsoft Copilot), or custom development?
  • Cost structures: Pay-per-token, subscriptions, infrastructure costs, or enterprise licensing?
  • Privacy and sovereignty: When do legal or regulatory requirements mandate private deployment?

Without a structured approach, organisations make decisions based on popularity, price, or technical enthusiasm—missing critical requirements around privacy, compliance, integration, or long-term viability.

What This Guide Covers

This guide walks through a systematic decision framework:

  1. Requirements Definition — Understanding your business problem and non-negotiable constraints
  2. Solution Landscape — Mapping the types of AI solutions available
  3. Build vs Buy vs Embed — Deciding between custom development, procurement, or platform-native AI
  4. Provider Selection Criteria — Frameworks for comparing ChatGPT, Claude, DeepSeek, and alternatives
  5. Deployment Model Selection — Public cloud, private, hybrid, or on-premise decisions
  6. Total Cost of Ownership — Understanding true costs beyond sticker price
  7. Legal and Compliance Considerations — Privacy, data sovereignty, regulatory requirements
  8. Integration and Architecture — Fitting AI into your enterprise technology landscape

How to Use This Guide

This is a decision support tool, not a prescription. Each organisation’s needs differ based on:

  • Industry and regulatory environment
  • Existing technology landscape
  • Risk appetite and maturity
  • Budget and resources
  • Strategic objectives

Use this guide to:

  1. Structure your decision process with frameworks and checklists
  2. Identify critical questions you need to answer before committing
  3. Evaluate options systematically against your requirements
  4. Avoid common pitfalls that derail AI initiatives

Ready to Assess Your AI Readiness?

Before selecting solutions, ensure your organisation is ready to govern and operate AI safely. See our AI Readiness Assessment to evaluate your maturity across 15 critical dimensions.

What’s Next?

If you’d like support navigating AI solution selection, architecture design, or vendor evaluation for your organisation, please get in touch.

Guide Sections