Zehra Cataltepe is the CEO of TAZI.AI an adaptive, explainable Machine Learning platform. She has more than 100 papers and patents on ML.

As an executive in a midsize company, you may find yourself facing a common challenge: limited resources. You may have a small team of data engineers/scientists and software developers, and your data might be limited.

However, these constraints should not deter you from embarking on your AI solution journey. Here, I will outline a step-by-step approach to successfully start and continue your AI solution journey, keeping in mind the costs and risks of different approaches.

This article contains the steps of the cross-sell/up-sell journey and the identification of what other product or product features to offer to your existing clients. If you crack these, they can increase both your customer retention and profitability. Propensity prediction, getting new customers that are also profitable or anomaly/fraud detection, especially where you are not profitable, are some of the other AI journeys you can embark on.

As you will see below, your AI journey has to contain many more steps than just building one good prediction model, so generative AI will probably not replace you or your decisions in the very near future.

Step 1: Identify your problem.

The first step in an AI solution journey is to clearly define the problem. For instance, you may want to identify suitable customers for cross-selling in a complex, changing portfolio, especially those at high risk of churn. Customers getting great value from your product may be open to trying new things, increasing revenues without customer acquisition costs.

A continuously updated AI solution can transform customer identification and clustering. Analyzing data points enables faster, more effective segmentation and targeted marketing, maximizing cross-selling opportunities.

When identifying the problem, make sure that you are forward-looking in time and include as many relevant stakeholders as possible so that there is agreement on what the problem is.

AI journeys rarely succeed if the problem has not yet been identified or is not urgent. Methods like detailed analysis or modeling on your financials, internal questionnaires or Gartner’s use case prisms might be helpful.

Step 2: Understand your challenges.

Understanding your challenges is key to finding the right AI solution. Your challenge may be identifying customers likely to buy additional products by uncovering complex data patterns. You may also need to determine the best time, method, message and person to contact each customer for optimal results. If you aim to reduce churn or increase cross-selling, identifying clients likely to churn or benefit from your product is a challenge to address.

Data quality is always an issue. You only truly understand your data and its gaps after using it in AI models and seeing where they fall short. Improving data quality is an iterative process involving data preparation, model building, insights, deployment and reiteration.

Having a team with the right mindset is even more challenging than data or prediction problems. Ensure your team’s involvement and empower them to make and own key decisions.

Step 3: Choose the right AI solution.

Choosing the right AI solution requires considering its capabilities and costs. AI solutions can vary in price, so consider both upfront and ongoing costs. The chosen solution should address your problem and challenges within your budget. Rapid prototyping is important to quickly identify where AI works and where it doesn’t, allowing you to switch use cases if needed.

Consider your needs when your AI is in production. If you need frequent model updates due to changing business conditions or new ideas, choose solutions with continuous learning and human involvement to reduce costs.

If cloud charges are a concern, consider hybrid architectures or tech vendors who work with you to move the right data, optimized for the next step, instead of all the data.

Step 4: Integrate the AI solution.

Integration of the AI solution into your existing systems is a crucial step. Look for solutions that offer seamless integration, allowing for real-time and adaptive export and distribution of leads to your sales agents. Integrating new data sources should also be supported since available data and what you need will change over time.

Look for solutions that offer training to both your technical team and the end users of the solution. When you integrate the end users right, through technologies such as a human-in-the-loop, they will keep giving feedback, allowing you to improve your solution.

Step 5: Analyze and adjust.

The final step is to analyze the outcomes and adjust your strategies accordingly.

Make sure that you have easy-to-use and personalized dashboards or portals to visualize data, predictions, results and value. This allows executives and end users to really see the value and where things are not moving right so that you know what to adjust. Seeing value and return on investment continuously also allows the whole team to be motivated to do more; it is easier to be motivated if all can see a $20 million annual value coming out of an AI solution and their efforts.

Adopt the AI solution based on regular user feedback. Simple changes, like adding or removing variables, can improve model performance and business adoption. As you see value in AI, scaling should be easy. Use previous solutions’ data and experience, and let your internal team improve the AI solution instead of relying on costly vendor consultancy.

Even with limited resources, you can successfully embark on your AI solution journey now. The key is to clearly identify your problem, understand your challenges, choose the right AI solution, integrate it into your systems and continuously analyze and adjust your strategies. With this approach, you can maximize your opportunities and minimize your risks, leading to successful outcomes.

Zehra Cataltepe

Forbes Councils Member

Forbes Technology Council

Also Published on Forbes: https://www.forbes.com/sites/forbestechcouncil/2023/09/14/how-to-successfully-embark-on-your-ai-solution-journey-a-step-by-step-approach/