AI is everywhere

Spending on generative AI grew significantly this year. This is creating opportunities for products of all types. With all the AI in the air, AI will inevitably come to your product soon.

Is your product ready for AI? Should you treat AI features like any other new product feature?

Before rushing to add AI features, preparing your product for AI is important.

Why product fitness for AI matters

Getting your product fit for AI is a proactive and strategic step. AI in your product has some unique risks:

• AI can produce surprises in real-life usage: the models don't always produce the same result

• Data dependencies: poor data can make AI features ineffective or harmful

• Compliance concerns: privacy and legal requirements can be stricter for AI than traditional features

• Business model impacts: AI can introduce strategic pricing changes

• Continuous updates: AI isn't a static feature - models require updates to stay relevant

• The stakes are higher: an AI mistake can damage your product's reputation or lose customer trust

Another consideration is the cost of rework later. Pausing to address critical operational issues can significantly impact your product's business!

The product AI fitness strategy

Addressing your product's fitness for AI is strategically important as you add AI features.

However, there is tremendous pressure to embed AI in all types of products. The benefit is capturing business while customers are allocating budgets to AI. No product manager wants to slow the business growth from AI!

A winning strategy is to initiate a parallel workstream to get started on product fitness for AI. As you build your business case for the new embedded AI features, you can include key product fitness requirements.

The AI readiness checklist for product managers

Whether you have AI features near term or in the future, you can take steps to protect your product from the new risks from AI features.

The major categories of AI readiness are:

1. Data readiness

2. Infrastructure support

3. AI strategy alignment

4. Team readiness

5. Feature readiness

6. Risk management

7. Go-to-market readiness

8. Monitoring and iterating

A unique aspect of AI features is the post-launch requirements to keep the product healthy. A few of the ongoing post-launch items to monitor are:

• Making sure the data used in the AI features stays clean and in compliance

• Scaling of the AI workloads

• Customer and business goals for AI are being met

• AI developments are monitored for impacts on your solution

• Ongoing audits and governance checks

• Customer feedback loop

Often product managers are tasked with monitoring after the launch of new features.

In the case of AI, product managers need data management and AI experts to assist with ongoing guidelines for safe AI usage.

Whether you have AI in your product or not, this checklist can save you rework in the future. With AI infusing so much in high tech, an AI-ready product foundation gets people and processes ready to spring into action when needed.

How to start preparing for AI-Readiness

Before you are caught off guard by AI developments, you can take steps to make sure your product is fit for AI features. Groundwork can begin now by using the checklist to evaluate your product's readiness.

Some of the AI readiness questions will need research and will provide a good reason to collaborate with data management experts, engineering, quality, and legal teams.

After doing the AI readiness assessment, you will have a good picture of your product's readiness for AI features. Depending on the AI features in your product and the readiness assessment, you can determine the priority for handling AI readiness. The table below shows the priority based on the assessment and features:

If your product has a high dependency on AI and the readiness is low, then you'll need to put priority on readiness. Otherwise, continue to monitor your readiness and push for more progress.

This article highlights the key areas for AI readiness, but if you want to go further, here is a starting checklist to evaluate your product today (paid subscribers only). This early access version includes AI readiness categories and 40+ targeted questions to assess your product.

Conclusion - The hidden costs of being unprepared

AI features may unlock new opportunities, but without preparation, the risks can outweigh the rewards. Neglecting your product's fitness for AI can lead to costly rework, compliance challenges, and loss of customer trust. By proactively addressing readiness, product managers can ensure their product isn’t just riding the AI wave but leading it.

AI is more than a feature—it's a shift. Make sure your product is ready to thrive in the AI-driven future.

This article was originally published here.