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Artificial intelligence (AI) can help companies identify new opportunities and products, and stay ahead of the competition. Senior software managers should understand the basics of how this new technology works, why agility is important in developing AI products, and how to hire or train people for new roles.

Zorina Alliata spoke about leading AI change at OOP 2023 Digital.

In recent studies, 57% of companies said they will use AI and ML in the next three years, Alliata explained:

Chances are, your company already uses some form of AI or ML. If not, there is a high chance that they will do so in the very near future in order to stay competitive.

Alliata mentioned that AI and ML are increasingly being used in a variety of industries, from movie recommendations to self-driving cars, and are expected to have a major impact on businesses in the coming years.

Software leaders should be able to understand how the delivery of ML models is different from regular software development. To manage the ML development process correctly, it is important to have agility by using a methodology that allows for quick pivots, iterations, and continuous improvement, Alliata said.

According to Alliata, software leaders should be prepared to hire or train for new roles such as data scientist, data engineer, ML engineer. She mentioned that such roles might not yet exist in current software engineering teams, and they require very specific skills.

InfoQ interviewed Zorina Alliata about adopting AI and ML in companies.

InfoQ: Why should companies care about artificial intelligence and machine learning?

Zorina Alliata: AI and ML can help companies to make better decisions, increase efficiency, and reduce costs. With AI and ML they can automate repetitive processes and improve the customer experience significantly.

A few years ago when I had a fender bender with my car, I had to communicate with my insurance company through phone calls, and take time off work to take my car to specific repair shops. Just last year when my teenage son bumped his car in the parking lot, he used his mobile app to communicate with the insurance company right away, upload images of the car damage, get a rental car, and arrange for his car to be dropped off for repairs by a technician. He could see the status of the repairs online, he received automatic reports and his car was delivered at home when fixed. Behind his pleasant experience, there was a lot of AI and ML – image recognition, chatbots, sentiment analysis.

Another thing companies can benefit from is mining insights from data. For example, looking at all your sales data, the algorithms might find patterns that were not previously known. A common use for this is in segmenting and clustering populations in order to better define a focused message. If you can cluster all people with a high propensity to buy a certain type of insurance policy, then your marketing campaigns can be much more effective.

InfoQ: What should senior software managers know about artificial intelligence and machine learning?

Alliata: Let me give you an example. We sometimes do what we call unsupervised learning – that is, we analyse huge quantities of data just to see what patterns we can find. There is no clear variable to optimize, there is no defined end result.

Many years ago, I read about this airline that used unsupervised learning on their data and the machine came back with the following insight: it found that people who were born on a Tuesday were more likely to order vegetarian meals on a flight. This was not a question anyone had posed, or an insight anyone was ready for.

As a software development manager, how do you plan for whatever weird or amazing insight the algorithms will deliver? We just might not even know what we are looking for until later in the project. This is very different from regular software development where we have a very clear outcome stated from the beginning, for example: display all flyers and their meals on a webpage.

InfoQ: What can companies do to prepare themselves for AI adoption?

Alliata: Education comes first. As a leader, you should understand what the benefits of using AI and ML are for your company, and understand a bit about how the technology works. Also, it is your task to communicate and openly discuss how AI will change the work and how it will affect the people in their current jobs.

Having a solid strategy and a solid set of business use cases that will provide real value is a great way to get started, and to use as your message and vision.

Promoting lean budgeting and agile teams will help quickly show value before large investments in AI resources and technology are made.

Establishing a culture of continuous improvement and continuous learning is also necessary. The technology is changing constantly and the development teams need time to keep up with the newest research and innovation.