How Can I Scale AI-enhanced Product?

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Artificial intelligence (AI) is revolutionizing business, but that doesn't make it valuable for all companies looking to add value and growth. The challenge is knowing when and how to use AI intelligently.

Dr. Jerrold Jackson is Vice President and Director of Machine Learning and Data at Exos, a human performance and wellness company, where he uses AI to deliver personalization and optimize the customer experience in real time . At the Georgian ScaleTech conference, he shared his thoughts on the fastest and most efficient way to add value by adding AI capabilities to your products and services.

Drawing on his experience designing and implementing data strategies at Exos and several other rapidly changing industries, Jerrold provided concrete examples of when and how AI can evolve in his organization, as well as concrete ways to measure success. . Below we have summarized some of the most important ideas from his presentation, e.g. B. the right way to assess AI opportunities and scale your AI product.

Is the AI ​​suitable?

AI can help businesses deliver great value to their customers, but it's not the right tool for everyone. So how do you assess whether AI is the right solution at the right time? Jerrold said the answer is often data dependent.

AI is data-intensive and requires constant power, so it is best deployed in industries where data is abundant and accumulates quickly, such as: B. Fintech or Adtech, where it can be used to train and refine machine learning algorithms.

“Many growth-stage companies do not inherently have big data or sufficiently dynamic and common data to power AI methods and systems,” Jerrold said.

This does not mean that an AI solution is not an option for them. Growth-stage businesses can still benefit from smaller, high-quality datasets or prepare for AI for the future. If you think AI will be essential to bringing value to your business, Jerrold recommends planning today for the data you'll need later.

 

Whether you're taking the plunge and embracing AI today or planning for the future, Jerrold said organizations need to proceed with caution. AI systems are a big investment and results can take time. “AI user experience is not magic. It takes a long time to develop and refine the underlying skills,” he advised. “Be realistic and sober.”

 

HOW TO EVOLVE AI

An organization decided to invest in AI. How should you expand your AI efforts? Jerrold shared the following five tips based on his experience bringing ML and AI capabilities to Exos and the financial services and ticket resale market.

Develop clear use cases: The first step is to identify areas where ML and AI can make a difference. If you have a long list of applications or use cases, narrow them down by focusing on areas where the technology will have the greatest impact. “One way to accelerate ML and AI-based efforts is to name and clarify the use case or use cases,” Jerrold said.

Invest time and money: Cost can be a barrier to scaling AI. Although the technologies that power AI are increasingly affordable, they still come at a steep price. Time is another consideration as AI skill development and results take time to build. Jerrold compared AI adoption to planting a new garden: "Sometimes you can water it, you can invest in it, and you don't see immediate returns or growth," he said. declared. "It really takes time, so be patient."

Given the need for upfront investments both over time and monthly, Jerrold said it was important to show value immediately. He suggested aiming for small incremental wins, a strategy he uses at Exos.

At Exos, Jerrold focuses on areas of the business where AI can make a difference quickly, as well as areas that may pay dividends in the future. "AI-based use cases are new, but we also want to see the impact immediately. I decided on the use cases early on and now have AI in the product, year one , to generate recommendations and early personalization,” he said.

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