Today’s interview is with Matthew Nolan, the head of Product Marketing for the Decision Sciences division at Pegasystems, driving Pega’s portfolio of marketing technology, decision management, and customer engagement solutions. Matthew joins me today to talk about the democratisation of artificial intelligence (AI), what that means, the benefits and risks associated with that and some practical advice for leaders and practitioners looking to improve the experience that they deliver to their customers.

This interview follows on from my recent interview – Enabling everyone to have the ability to understand the hidden stories in their data – Interview with Dr Derek Wang of Stratifyd — and is number 384 in the series of interviews with authors and business leaders that are doing great things, providing valuable insights, helping businesses innovate and delivering great service and experience to both their customers and their employees.

NOTE: A big thank you goes out to the folks at Pega for sponsoring my podcast this month.

It’s almost time for PegaWorld iNspire, the annual conference from Pegasystems. Join them online for free on May 4 from 9 a.m. – 11:30 a.m. Eastern Time (that’s 2 p.m. – 4:30 p.m. UK time) to learn how the world’s most impactful companies are driving digital transformation. They’ll have compelling keynotes, demos, and case studies in a highly interactive virtual format and a few surprises as well. Go to www.pegaworld.com to register for free and check out the full agenda. I’ve attended the last several PegaWorlds in person, and virtually, and I can’t recommend it highly enough, so go register today! That’s www.pegaworld.com

Here’s the highlights of my chat with Matthew:

• Democratization of AI is about making it easier for people to use AI to accomplish day to day tasks and to achieve real value.
• It starts with first party data and being able to easily capture the information that’s coming in from channels that you own and conversations you’re having with your customer and connecting that to the experiences they have with your brand right across the whole life cycle.
• Democracy of any form is desirable because it changes the distribution of power.
• If you don’t do that then it becomes another system of power. When you have a system of power, the primary objective of a system of power is to protect its own power.
• This type of technology and the ability to learn at a massive rate, very quickly about everybody all over the place is going to be one of the things that drives regulation and governmental oversight over the next 50 years.
• AI has to be an enabling technology rather than a controller.
• Low code is probably that next logical step… making it easier for developers to integrate AI predictions into a supply chain or making it really simple for a marketer to onboard a new data source, instantly activate that information and be able to then quickly use it in a model and decide exactly what to show a customer on a website, say, or when talking to somebody in a call center.
• Right now, AI is like a ‘dark art’. There’s a huge gap in quality and efficacy around AI tools and, as such, it’s hard to get up and running and operationalized.
• Don’t focus on the tech as much as making that tech available and easy to use, then adoption goes up and you see it proliferate much, much faster.
• Start from the vision of what you want to try and achieve or the kind of problem you are trying to solve and then work backwards from there thinking about what what tools and data you need to facilitate the resolution of that situation.
• The major risks over the short term are things like ethical bias. But, from a business point of view, it’s the perception of bias as well. Bias and the perception of bias are two very, very different things.
• As a example of the possibilities, Commonwealth Bank, in Australia, over the last 12 months used their AI to identify people who the bank felt were in need of a repayment holiday because they were struggling, trying hard to make ends meet or maybe they were out of work. So, what they did was use the AI to reach out to them proactively make them aware that they were eligible for specific benefits. Over 125,000 people took advantage and postponed loan payments. Historically, you don’t see banks do things like that.
• People in the US are going to remember Verizon last year when they actually reached out to folks and offered free data to people who needed it when everybody was initially working from home and everyone had all a lot of bandwidth issues. Now, I’m not a Verizon customer but nobody offered me free data and I’m still kind of peeved about it.
• Oganizations are two or three or five years ahead of legislation. So, organizations have to self govern. They can’t default to just staying ahead of the law. That is way, way too low a bar. They have to be aware of how their AI is being used. They have to look actively to mitigate bias, they have to be transparent and they have to put the customer first.
• I think the companies that do that will eventually become the ones that people trust and will thrive over the long term as this type of technology takes off.
• Check out Pega’s whitepaper: Responsible AI: Great Power Requires Greater Accountability.
• However, a lot of people will talk about it but it’s more about what they do than what they say.
• In the future, we’ll see more and more technology layer into people’s lives, organizations will have more and more data to use to understand them and what they need. There is going to be a massive surge in digital signals and it’s going to be coming off everything. We’re going to see 10 or 100 or 1000 times what we see right now from IoT, from your devices, from your phone etc. That’s the next frontier of service. Brands are going to use those signals to understand when customers are stuck, when they’re frustrated, when they are struggling to understand something and they are then going to proactively respond to those situations.
• Royal Bank of Scotland always talk about the idea of getting ahead of service problems, like scanning through data, mining through information to get ahead of problems and then warn the custom about things like if their card is not going to be working if they’re traveling or something like that.
• Matt’s advice: Regardless of whatever channels you’re going to use to service your customers you need to be gathering the data that you already have and make that a priority for your business as that data is a gold mine of great context around customers. Use it to power everything from outbound communications to insights about how to interact with the customer over the long term. It’s going to make all the difference in a service experience and it empowers the whole life cycle of the customer relationship.
• Matt’s Punk CX word(s): Carrot juice.
• Matt’s Punk CX brand: Apple (20 years ago).

About Matthew

Matthew Nolan is the head of Product Marketing for the Decision Sciences division at Pegasystems, driving Pega’s portfolio of marketing technology, decision management, and customer engagement solutions. Before joining Pega, Matt was General Manager of the National Data Cooperative at Target Analytics, and served as Product Director for Analytics & Data Services at Blackbaud, Inc. A life-long marketing practitioner and analyst, he is a regular keynote speaker, an active supporter of the American Red Cross, a green-blooded Boston Celtics fan, and has held membership in the Society for American Baseball Research (SABR) since 2004.

Find out more about Pega at www.pega.com, go to www.pegaworld.com to check out the agenda and register for free, say Hi to them and Matthew on Twitter @pega and @NolanMatthew and feel free to connect with Matthew on LinkedIn here.

Image by Gerd Altmann from Pixabay