AI Transformation and Its Impact on Product Management

As I look to the future and imagine what’s to come regarding AI products, I feel tremendous inspiration and optimism about AI’s ability to help us out of some of the greatest challenges that face humanity. I moderate a monthly talk with Women in AI called WAITalks. Many of my questions during these monthly talks are recurring questions, largely centered on how the speakers broke into the field, what excites them most about AI, and what they wish others knew about their area of AI. There’s a lot of beauty and insight from how the various women working in AI, from research to corporate to entrepreneurship, answer the same set of questions.

One of our March 2022 speakers worked in AI policy at Meta. Because so much of her work involves ethics, we spent a great deal of time discussing the risks and inherent problems AI poses. After some time on that, I wanted to know what someone in her position looks forward...

Money and value – how AI could revolutionize our economic systems

AI has been no stranger to fintech as well as our greater economic systems. We’ve seen the rise of cryptocurrencies develop in concert with this change in how the financial industry is operating. Smart contracts specifically have been a huge motivator for crypto and blockchain adoption. This isn’t a book about crypto, but it does signal a change in how financial industries and economic systems are fundamentally operating.

Artificial intelligence (AI) and machine learning (ML) are excellent tools for optimization, and there are few more compelling use cases for AI/ML than the optimization of profits. The financial industry has been leveraging quantitative analysts or quants for a long time. Quants do statistical and mathematical modeling for financial and risk modeling problems and, in many cases, it has been a profitable career for those that were interested in the sexiest job of the 21st century...

Goods and services – growth in commercial MVPs

Now the fun stuff! One of the great blessings of AI/ML is seeing just how creative we humans can get with it. In the previous section, we wanted to start with finance and business because this is the heart of the capitalist free market – everyone is in the business of making money at the end of the day, and product management is, once again, an inherently commercial role. Let’s take one step away from that and briefly explore the world of AI commercialization. What we mean by this is that various AI use cases are appearing across various industries and sectors. There are many to choose from, and we have no doubt someone out there will have all the fun in the world writing a book about all the creative and fun new ways you can use AI/ML across a wide variety of commercial industries, but here, we will only use a few key examples that we find particularly inspiring as promising, early MVPs.

In keeping with the theme...

Government and autonomy – how AI will shape our borders and freedom

It’s not all fun and games. The immense availability of data and AI simultaneously opens us up to the risk of authoritarianism and the rise of oppression, and the collective empowerment to combat threats to democracy across the world. At the moment, we have some striking contradictions of power and protection being exerted in very different ways, based on a system of shared societal values. In this section, we will be looking at how AI will be leveraged in governmental capacities and what it means for all of us as consumers and makers alike.

Governments will increasingly need to focus on preserving their country’s ecosystems and the fallout from climate change, and with that focus, there will need to be some degree of investment as well. The private sector can only do so much, and we hope that governmental bodies will use their influence for the betterment of their citizens. Let’s take...

Sickness and health – the benefits of AI and nanotech across healthcare

AI continues to be incredibly successful when applied to the medical and healthcare industry. Drug discovery and development companies such as CytoReason, DeepCure, and BullFrog AI help their customers find and analyze new molecular compounds to create novel drugs for some of the most pressing illnesses that plague humanity, shorten time to market for these new drugs, and assist with the patenting process. Companies such as Standigm enable AI workflows to leverage AI through the journey of highly customizable target identification and lead generation. Before AI, the journey to discovering a new drug, conducting clinical trials, and bringing the drug to market might have taken upward of 10 years.

We also see personalization and prediction being applied to personal care through the use of AI, which is particularly exciting when you consider the doctor shortage we’re experiencing worldwide. Wouldn...

Basic needs – AI for Good

One thing that really struck me about the data science and AI/ML community when I first joined was how communal it was. My prior career was in sales and account management, and I took how competitive it was for granted. I was struck by the benevolence of the community. There were so many open source projects you could get involved in. You could put your projects up on Kaggle and win competitions. You could find an almost infinite supply of solutions to problems on Stack Overflow. I found a lot of success reaching out to people, who shared their perspectives on their area of AI. Never was this more apparent than when I reached out to potential speakers to host a panel or a workshop to teach others. It makes this field all the more compelling because if you do want to focus on a particular AI solution, you can find lots of friends along the way to join your cause and support you.

You’ll likely see the term AI for Good used by organizations that...

Summary

This concludes Part 1. We started with an introduction to AI and the infrastructure required to support it, went into the weeds of model maintenance and the particulars of ML and deep learning, saw a mix of applications and business model examples of AI products, and concluded with a glimpse into where AI is going next. Part 2 will expand on the AI native products themselves by focusing on what it takes to understand, ideate, create, and productize AI. We will also explore how AI products can be customized and how performance can be optimized, as well as going into some examples of common pitfalls and successes a product manager can run into with the AI native product.

In the next chapter, we will be looking at what areas are essential when you’re building an AI-native product. We will be looking at the particulars of managing a product from the ground up, with certain AI considerations and what product managers will need to account for as they begin the process of...

Additional resources

If you’re in the US and at risk of self-harm, please check out the following resources:

• Crisis Text Line: Text CRISIS to 741741 for free, confidential crisis counseling
• The National Suicide Prevention Lifeline: 1-800-273-8255
• The Trevor Project: 1-866-488-7386

For those outside the US, check out these resources:

The International Association for Suicide Prevention lists a number of suicide hotlines by country. You can find them by going to their website (https://findahelpline.com/i/iasp). Also, check out Befrienders Worldwide (https://www.befrienders.org/need-to-talk).

References

• The Role of Big Data, Machine Learning, and AI in Assessing Risks: a Regulatory Perspective: https://www.sec.gov/news/speech/bauguess-big-data-ai
• Artificial Intelligence, Machine Learning, and Big Data in Finance: https://www.oecd.org/finance/financial-markets/Artificial-intelligence-machine-learning-big-data-in-finance.pdf
• Data Scientist: The Sexiest Job of the 21st Century: https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century
• Bowery Farming: https://boweryfarming.com
• Square Roots: https://www.squarerootsgrow.com/
• Plantix: https://plantix.net/en/
• Peat: https://peat.technology/en/
• IBM AI for Good sponsorship focuses on AI in service of the planet: https://www.ibm.com/blogs/journey-to-ai/2021/11/ibm-ai-for-good-sponsorship-focuses-on-ai-in-service-of-the-planet/
• Google AI FOR SOCIAL GOOD: https://ai.google/social-good/
• H2O.ai AI 4 Good: https://h2o.ai/company/ai-4-good/
• Microsoft AI for Good: https://www.microsoft...

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