Building vs. Buying AI Solutions: A Decision-Making Framework

Is your organisation bleeding money because of a misfiring AI implementation strategy? Are you losing clients to competitors with better answers to questions about AI adoption? You’re not alone.

Every day, we see businesses paralysed by the build-or-buy dilemma. This choice reaches beyond technology to determine your organisation’s competitive advantage.

The stakes are enormous. According to McKinsey, successful AI implementation can deliver a 20-25% increase in EBITDA. Yet Gartner reports that 85% of AI projects fail to deliver on their promise. The gap between success and failure often emerges from the right build-or-buy decision.

Here is a framework that provides clarity where most organisations find only confusion.

The True Economics of Build vs. Buy beyond the price tag.

The real cost of AI implementation extends far beyond initial investments. Our analysis reveals a consistent pattern of costs:

Initial Development or Purchase: Building custom solutions typically costs 3-5x more upfront than purchasing existing ones. But this simplistic comparison misleads many executives.

Continuing Maintenance: Custom-built solutions require up to 35% of initial development costs in annual maintenance. Purchased solutions typically require 15-20% in subscription fees.

Hidden Costs: Return on investment calculations must include training (1,500+ hours for custom solutions), integration (40% more complex for purchased solutions), and security compliance (critical for both approaches).

The true cost comparison for middle market companies and upwards, looks like this:

For mid-market companies, purchased solutions typically deliver faster ROI. Enterprise organisations with complex requirements and established technology teams often find long-term economics favour custom development.

Ownership vs. Agility: Balancing Strategic Control with Time-to-Market

Time-to-market represents a critical advantage in AI implementation. Data shows:

Custom development takes 6-12 months from concept to production. Purchased solutions can deploy in 2-4 months.

This presents a strategic dilemma. Is the competitive advantage of a custom solution worth the opportunity cost of delayed implementation?

A Financial Services client recently faced this exact challenge. They adopted a purchased solution for their customer service AI to use as a stop-gap while developing custom algorithms for longer-term deployment.

This strategic balancing delivered immediate efficiency gains while protecting their core competitive advantage in the long term.

Strategic control factors to consider:

• Intellectual Property: Custom solutions provide complete ownership of unique algorithms and models.
• Partner Dependency: Purchased solutions create reliance on partner roadmaps and pricing changes.
• Competitive Advantage: Does the AI function represent core business differentiation or operational efficiency?
• Market Dynamics: Fast-moving sectors demand speed over perfection.

Compatibility and Customisation: Evaluating Your Technical Landscape

Your existing technical ecosystem dictates much of your build-vs-buy decision. The key factors include:

Integration Requirements: How deeply must the AI solution connect with existing systems? Purchased solutions often automate a single task, rather than deliver end-to-end process automation.

Data Architecture: Organisations with highly structured, centralised data environments find it easier to integrate purchased solutions. In contrast, adding another technology to a jumble of legacy purchases, will not reap rewards.

Security Requirements: Regulated industries face additional compliance hurdles with external vendors. Private clouds are an option if you do not host your own data.

Customisation Needs: The degree of customisation required often determines your strategic choice. This is why purchased options often focus on single, internal workflows. The more complicated your product, the more customised your automation of customer service must be.

Our analysis reveals three broad levels of customisation:

• Light customisation (UI changes, workflow adjustments): Purchased solutions excel.
• Moderate customisation (business rule modifications, integration adaptations): Either approach works. Custom development is preferable.
• Heavy customisation (unique algorithms, proprietary processes): Custom development required.

A global manufacturing client demonstrates this principle perfectly. The attempt to adapt a purchased solution for its unique quality control process resulted in a 14-month implementation nightmare. To fix this they had to scrap the purchased system and build a custom application, which deployed successfully in just 5 months.

Talent and Culture: Is Your Organisation Prepared?

What is the most overlooked factor in the build-vs-buy decision? Your organisation’s readiness.

Building custom AI solutions demands specialised talent:

• Data Scientists
• ML Engineers
• AI Ethicists
• Domain Experts
• DevOps Specialists

The average enterprise-grade AI project requires 7-10 specialised roles. This represents a significant investment, with AI talent commanding premium salaries (30-50% above traditional IT roles).

Beyond talent, organisational culture determines success. Our assessment of 75+ AI implementations identified these critical success factors:

• Executive sponsorship with technical understanding
• Data-driven decision-making culture
• Willingness to iterate and refine solutions
• Cross-functional collaboration capabilities

Organisations scoring low on these factors achieve 3x better outcomes with purchased solutions than with custom development.

Hybrid Solutions Make Sense

The build-vs-buy decision isn’t binary. For 63% of our clients, hybrid approaches deliver optimal results.

Effective hybrid strategies include:

Component-Based Development: Building custom applications on top of purchased AI frameworks.

Phased Implementation: Starting with purchased solutions while developing custom components for future integration.

Core-and-Spoke Models: Building custom solutions for core functions while purchasing peripheral capabilities.

Your 5-Step Decision Framework for Build vs. Buy

Here’s an action plan for making this critical decision:

Step 1: Define Core Business Objectives and Success Metrics

Articulate exactly what success looks like. Link AI initiatives to business outcomes with measurable and meaningful KPIs.

Step 2: Detail Technical Requirements and Constraints

Document integration needs, data architecture, security requirements and scalability expectations.

Step 3: Assess Organisational Capabilities and Timeline

Evaluate your talent pool, cultural readiness and implementation timeline constraints.

Step 4: Calculate Comprehensive TCO for Both Options

Project 3-year total cost of ownership, including all hidden and opportunity costs.

Step 5: Evaluate Strategic Alignment and Competitive Considerations by Consulting with Experts

Determine if the AI function represents a core business differentiation requiring custom development. Speak with AI Consultants who have done this for other businesses already. 

You can book a free AI Consultation call with us and we’d love to help.

The Decision That Shapes Your AI Future

The build-vs-buy decision shapes your current implementation and your organisation’s AI trajectory for years to come.

The wrong choice costs millions in wasted investment, months of lost market opportunity, and erodes competitive position.

The right choice accelerates your AI credibility, delivers measurable business value and positions your organisation to win more clients.

Our team has guided hundreds of organisations through the automation decision process. We’ve seen spectacular successes and aided recovery from the painful failures.

Make Your Decision with Confidence

Deciding between building and buying your AI solution is a critical decision that requires a strategic approach. The right choice can streamline your operations, reduce costs and ultimately elevate your business.

Still struggling with the complexities of this decision for your specific situation?

We provide a free 60-minute consultation with our AI experts to apply this framework to your unique challenges. We’ll help you identify the approach that aligns with your business objectives, technical requirements and organisational realities.

Book Your Free AI Strategy Consultation

Join the organisations we’ve guided to successful AI implementation.