Today’s interview is like an interview I released a couple of weeks ago and features two, separate interviews that I conducted on a recent trip to Pegaworld iNspire held in Las Vegas.
The first interview is with Kerim Akgonul, the Chief Product Officer at Pega. This is swiftly followed by a chat with Dr Peter Van Der Putten, who is assistant professor of AI at Leiden University in The Netherlands and Director of the AI Lab at Pega.
I talk to them both about their highlights from the event and what’s top of mind for them in the service and experience space right now. Unsurprisingly, we cover the automated enterprise, demos featuring western omelettes, process mining, how to get the most value out of AI and, of course, how gen AI will impact all of this.
This interview follows on from my recent interview – Revisiting the Big Ass Fans story and what happened next – Interview with Carey Smith of Unorthodox Ventures – and is number 477 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.
Highlights of my chat with Kerim:
- Kerim has been with Pega for 30 years. Pega is 40 years old this year.
- Although the title of his keynote at Pegaworld 2023 was ‘The times they are AI changing’, he’s not really much of a Bob Dylan fan.
- Kerim’s main stage demo featured a cook-off against Don Schuerman making a Western omelette.
- When the ChatGPT eruption happened, they organised a GPT-athon (hackathon), and they came up with 128 projects.
- This forced them to step back and first think about how they evolved their architecture to make sure it could deliver against an effectively unlimited set of use cases and bring it into an approach where it is safe and secure.
- The stuff that you’re getting from Gen AI is not 100% accurate. It has high accuracy, and that’s great from a performance and efficiency perspective. But that’s also why, and particularly in highly regulated industries, for Pega, there will always be a human in the loop.
- The human-in-the-loop concept and having visibility into how AI makes decisions and what selections it makes is a critical aspect in all of this.
- We all know in software, it’s easier to make something that works better than it is to build something that is actually truly useful and robust.
- The layer cake part of Pega’s platform gives clients the opportunity to manage the variety of compliance and regulatory landscapes and control that by geography, industry or even business unit.
- The idea of process mining is to be able to provide a graphical visualisation to understand what systems actually participate end to end in a process to help people to analyse what truly happens in the organisation i.e. where is the money spent? where is the time spent? where is the bottleneck? where and what are the exceptions?
- The way it works is that it basically sniffs out log files, and it looks at all sorts of processing data across all the different applications that organizations use and applies AI to the analysis of that data.
- Operational efficiency is code for work done for less money.
- Kerim’s best advice: Capture your vision of what you want the experience to be, and then everybody can work towards that.
Highlights of my chat with Peter:
- Peter focuses on how clients can drive more value through the use of AI for specific use cases.
- He also focuses on how Pega can transform itself and the products and services it offers through AI. e.g. Process AI was launched two years ago and is all about how you put more intelligence into processes and workflows to optimise efficiency and effectiveness.
- The autonomous enterprise is like a North Star vision of where businesses are going and how businesses are developing into self-optimising businesses.
- If we can have autonomous cars, why can’t we have autonomous enterprises that also self-optimise towards goals?
- It’s really about what outcomes we can improve. And how can we transform business to become more & more autonomous?
- When it comes to generative AI, embrace the possibility and embrace the excitement, but don’t get carried away by the hype.
- At some point, you reach all the benefits you can get through automation. Then, you have to start working smarter. So, you put more intelligence into your interactions and into your processes. But then the question is, what’s after that? So, paint me a picture of what that might mean or what that could look like, and this is when we get closer to a picture of the autonomous enterprise.
- Peter illustrates what this could look like for an insurance company intelligently processing claims, optimising processes and highlighting potential fraudulent claims whilst also maintaining human oversight and operating with a fixed set of agents.
- If you have the intelligence, why not use it early in the process for self-service or even detecting customer service issues before customers even reach out to you? Or maybe in operations to make the process more effective, efficient, etcetera.
- We need to redefine AI. It’s not just artificial intelligence. It should be actionable intelligence – how do you make sure it gets used? It should also be augmented intelligence so it’s not replacing the human but is working shoulder to shoulder. Finally, it should also be accepted intelligence, and this alludes to responsible AI and making it trustworthy.
- We need to combine good old-fashioned rule-based AI with machine learning (gen AI) to get to automated decisions. This way, you have control over what it is that you’re going to decide.
- So, it’s not just machine learning but also machine reasoning. And, then next to that, you also need to think about things like transparency and do you understand what the decision was. Do you record all the decisions that are being made? And, can you measure the bias in a particular decision before you change your logical models or rules?
- Peter’s best advice: Focus on the outcomes. Don’t focus on the technology first, but rather focus on the outcomes that you want to improve. And is it something that really matters (to your customers, to your people and to your business)?
Kerim Akgonul is the Chief Product Officer at Pega and is responsible for delivering Pega’s full suite of products built on the Pega Infinity™ Platform. Kerim leads the company’s 1,000 plus team of engineers, product managers, designers, and architects, building best-in-class solutions across 1:1 customer engagement, customer service, and intelligent automation.
Kerim is focused on leveraging the latest technologies and development approaches such as low-code, AI, robotics, and cloud to support business users. He is an advocate for building software that makes the underlying technology transparent and serves the needs of the business. This focus on business impact has contributed significantly to the company being recognized as a leader in the major product and technology categories important to clients including low-code, customer relationship management (CRM), case management, intelligent automation, real-time analytics, and business process management (BPM).
Kerim began his career at Pega developing applications for customers in financial services and insurance, and he put his customer-centric perspective to work in establishing the company’s product management function. Early in the company’s history, Kerim recognized the power of connecting back-end operations to front-end, customer-facing applications. He continues to focus the product team on developing applications that allow business visionaries to innovate how their organizations interact with customers and help employees get work done more effectively.
Kerim holds a BS in Mathematics and Computer Science from Indiana University of Pennsylvania.
Peter van der Putten is assistant professor of AI, Leiden University and Director AI Lab at Pegasystems. Through his expertise in artificial intelligence and machine learning, Peter helps leading brands to become more ‘human’ by transforming into customer centric organizations. In addition to his role at Pegasystems, Peter is an assistant professor and creative researcher at the Leiden Institute of Advanced Computer Science (LIACS), Leiden University, The Netherlands.
He is particularly interested in how intelligence can evolve through learning in man or machines. Peter has an MSc in Cognitive Artificial Intelligence from Utrecht University and a PhD in data mining from Leiden University and combines academic research with applying these technologies in business. He teaches New Media New Technology and supervises MSc thesis projects.
Feel free to connect with Peter on LinkedIn here.