Building Your AI Strategy
The AI Opportunity Matrix: Build vs Buy vs Partner
Once you've identified valuable AI opportunities, the next strategic decision is how to pursue them. The build vs buy vs partner decision significantly impacts cost, time-to-value, and competitive positioning.
The Three Approaches
Build: Develop In-House
What it means: Your team develops custom AI solutions using internal resources.
Best for:
- Core competitive differentiators
- Unique problems with no market solutions
- When you have strong technical talent
- Long-term strategic capabilities
Considerations:
- Requires significant technical expertise
- Longer time to initial deployment
- Full control over solution and data
- Higher initial investment, potentially lower long-term cost
Buy: Purchase Solutions
What it means: Acquire ready-made AI products or platforms from vendors.
Best for:
- Common business problems (CRM, HR, finance)
- Rapid deployment needs
- Limited internal AI expertise
- Non-differentiating capabilities
Considerations:
- Faster time to value
- Predictable costs (often subscription-based)
- Limited customization options
- Vendor dependency and data considerations
Partner: Collaborate Externally
What it means: Work with AI consultancies, system integrators, or specialized firms.
Best for:
- Complex implementations requiring expertise
- Augmenting internal capabilities
- Pilot projects to prove value
- Knowledge transfer opportunities
Considerations:
- Access to specialized expertise
- Shared risk on uncertain outcomes
- Requires strong partnership management
- Potential knowledge gaps after engagement ends
Decision Framework
Strategic Importance Assessment
| Question | Build | Buy | Partner |
|---|---|---|---|
| Is this a core competitive advantage? | Yes | No | Maybe |
| Do market solutions exist? | No | Yes | Partial |
| Do we have internal expertise? | Yes | No | Some |
| Is speed critical? | No | Yes | Varies |
| Need deep customization? | Yes | No | Some |
The Build-Buy-Partner Matrix
Strategic Importance
Low High
┌─────────────┬─────────────┐
High │ BUY │ BUILD │
Internal │ (vendors) │ (in-house) │
Capability ├─────────────┼─────────────┤
Low │ BUY │ PARTNER │
│ (SaaS) │ (then build)│
└─────────────┴─────────────┘
Approach Comparison
| Factor | Build | Buy | Partner |
|---|---|---|---|
| Time to value | Long | Short | Medium |
| Initial cost | High | Low-Medium | Medium |
| Ongoing cost | Variable | Predictable | Variable |
| Customization | Full | Limited | High |
| Data control | Full | Varies | Negotiable |
| Talent needs | High | Low | Medium |
| Risk level | High | Low | Medium |
Hybrid Approaches
Most organizations use a combination of approaches:
Build + Buy: Use purchased platforms as foundations, customize with internal development.
Buy + Partner: Purchase solutions and engage partners for implementation and integration.
Partner + Build: Partner initially to develop capabilities, transition to internal team over time.
Key Questions for Each Approach
Before Building:
- Do we have the right talent?
- Can we retain this talent long-term?
- How long until we see results?
- What's the total cost of ownership?
Before Buying:
- Does the solution fit our specific needs?
- What are the data privacy implications?
- What happens if the vendor changes direction?
- How does pricing scale with our growth?
Before Partnering:
- How will we transfer knowledge internally?
- What happens when the engagement ends?
- How do we measure partner success?
- What intellectual property arrangements apply?
Common Mistakes to Avoid
Building when you should buy:
- Reinventing solved problems
- Underestimating development complexity
- Overestimating internal capabilities
Buying when you should build:
- Giving up competitive differentiation
- Accepting poor fit to avoid development
- Ignoring long-term vendor lock-in
Partnering without a plan:
- No knowledge transfer strategy
- Unclear ownership of deliverables
- No path to independence
Key Takeaway
The build vs buy vs partner decision should be driven by strategic importance and internal capability, not just cost or convenience. Most successful AI strategies use a portfolio approach—building core differentiators, buying commodity solutions, and partnering to fill capability gaps.
Next: Learn how to create a practical AI roadmap for your organization. :::