This week I wanted to focus on the big AI business decision: Build or Buy?

By which I mean, build your custom AI solutions in-house or buy existing, off-the-shelf ones from third-party providers. This choice isn't just about the tech, but about aligning with your company's goals, resources, and timelines.

Companies are spending millions on AI-powered SaaS tools—many of which go underutilized. The build vs. buy dilemma isn’t just about customization or speed; it’s about making sure your AI investments actually deliver value. Should you keep stacking SaaS subscriptions, or is it time to build something truly tailored to your needs?

Let's explore both paths to help you determine the best fit for your organization…

1 - Building In-House AI Solutions:

Opting to build your AI solutions internally offers several advantages:

• Customization: Develop solutions tailored precisely to your unique business needs.
• Competitive Edge: Proprietary AI can differentiate you in the marketplace.
• Data Control: Maintain full oversight of your data and its applications.

However, it also comes with challenges:

• Resource Intensive: Requires significant investment in talent and infrastructure.
• Longer Development Time: Building from scratch can delay deployment.
• Risk of Overestimation: You may overestimate your internal capabilities, leading to potential setbacks.

⚒️ When to Build:

• Your business requires highly specialized AI functionalities.
• You possess or can acquire the necessary in-house expertise.
• The AI solution is central to your long-term strategic objectives.

Here’s a real-world example from the Financial Times: Irell & Manella, a law firm, developed their own AI-powered Irell Programmable Patent Platform (IP3) to enhance the security and adaptability of their patent analysis.

2 - Buying Off-the-Shelf AI Solutions from Third Parties:

Purchasing existing established AI solutions can be advantageous:

• Speed: Accelerate implementation with ready-made tools.
• Cost-Effectiveness: Avoid the expenses associated with in-house development.
• Proven Performance: Utilize solutions that have been tested and refined.

However, there are considerations:

• Limited Customization: Off-the-shelf products may not meet all specific needs.
• Dependency: Reliance on external vendors for updates and support.
• Data Privacy Concerns: Sharing sensitive data with third parties can pose risks.

💰When to Buy:

The required AI capability is standardized across the industry. You need a solution deployed quickly. Internal resources or expertise are limited.

In the same FT example above, a different law firm, McDermott Will & Emery, leveraged third-party AI tools from eBrevia to analyze healthcare data, providing tailored market insights.

But there’s a third option: a hybrid approach.

3 - Hybrid Approach: The Best of Both Worlds:

Many organizations find value in combining both strategies, and outsourcing custom solutions where necessary.

Off-the-shelf solutions only go so far in each individual business context, and become increasingly expensive the more subscriptions your business has…

The underutilization of SaaS

Research indicates that companies often overspend on SaaS subscriptions, with a substantial portion of these tools remaining under-used. A 2023 report by Zylo reveals that companies waste over $17 million annually on underutilized SaaS applications… and you can bet that’s increased in the past couple of years with the increase in “AI Powered” platforms on the market.

Better to custom-build an AI solution to a specific business challenge or workflow that your team actually has, than continue racking up subscription costs for generic AI platforms in every department.

There’s no right answer here. The build vs. buy decision is multifaceted and context-dependent. By carefully evaluating your business’ specific needs and capabilities, you can choose a path that aligns with your strategic goals and resources.

You can use the Pollup ‘Build vs Buy Framework’ to help your decision-making:

It helps you choose the ideal mix of tools and services that align with both your business priorities and your broader vision for positive change.

• Strategic Fit: Does the AI solution directly support your core business objectives? Whether you need a standardized SaaS tool or a fully tailored approach, we ensure the solution aligns with your goals and drives tangible business value.
• Time-to-Market: How quickly do you need the solution operational? Every project has its own timeline. Some initiatives require rapid deployment, while others benefit from a custom-developed approach. We help you determine the timeline that best fits your unique situation.
• Resources & Costs: Do you have or can you acquire the necessary talent and infrastructure? We evaluate whether a quick, cost-effective, standardized solution is suitable or if investing in a custom approach is warranted given your internal capabilities. We consider available resources and both short-term and long-term costs to ensure maximum value from your investment.
• Data Sensitivity: Are there privacy or compliance issues to consider? If your data requires special handling, we design solutions that meet the highest standards of privacy and security, ensuring robust protection and compliance.
• Impact: How can you reach a solution in a sustainable way? We also focus on the broader influence of your AI choices. We identify tools that not only drive performance but also support your ESG goals and other impact initiatives, ensuring your technology investments contribute positively to both your business and the world around you.

I’d love to know how people are tackling this challenge? Do you know where to start?

If you’re stuck and feeling help, I’m happy to have a free discovery session and provide some insights. We offer an AI Empowerment Programme to help companies embed AI into their workflows: Just schedule some time here to discuss!

Leave a comment below!

All the best,

Caroline