Jason Angelides, Founder and President of Epoxy.ai, places a focus on the adoption of AI and ML in the gambling sector by looking at how to get started, the opportunities provided, how integral the adoption of each will become for all and much more.
SBC News: To begin, could you briefly elaborate on where we are currently at regarding the industry’s adoption of AI and ML solutions?
Jason Angelides: That is a great question and one deserves a thorough answer as there is a ton of noise, hype and confusion around the topic. The short answer is, the gaming industry is still in the early stages of AI and ML adoption, but things are certainly moving in the right direction.
By definition gaming companies are data businesses, and data businesses are extremely well positioned to leverage the power of AI. Data is part of almost every aspect of the gambling industry business, think trading, marketing, CRM and loyalty. However while most operators have data teams, the use of AI in these areas is limited with many still relying on legacy technologies and even manual processes.
Perhaps the area that is slowest to change, and one that can create significant value for customers and operators, is in the personalisation of the end user user experience around the needs of a specific customer. Personalisation is something that is foundational to other digital businesses such as e-commerce, music, tv and even retail, yet overall there is no operator that has implemented a cohesive, customer first strategy at scale.
Many are relying on brute force means to tailor content to individual groups or clusters of users to try to drive scale. For example the majority of tier-1 sportsbooks who, to support the need to create higher value more targeted parlay offers for their customers, and employ teams of editors to curate specific parlay bet markets that are displayed in the app. While this works, it is hard to scale and is impossible to provide the type of 1-1 type personalisation that AI can deliver and customers expect every time they bet..
Think of it as Amazon when it was just selling books. That’s kind of where we are now. The good news is that there are many more technologies at play and they are much more advanced, so implementation should be significantly faster and those that are early adopters will reap significant benefits.
“Globally consumers have become accustomed to personalisation interactions in their daily lives”
SBCN: Will this inevitably become essential for all businesses?
JA: I think it is indisputable how important AI is going to be for the gaming business, especially when it comes to creating meaningful differentiation and sticky experiences. There are hundreds of different digital brands providing online casino and sportsbook globally, and these are still almost entirely one-to-many solutions.
Globally consumers have become accustomed to personalisation interactions in their daily lives and they get frustrated when this doesn’t happen. The number one complaint of end users of online casino and sportsbook is the fact that the content and experience is not tailored to the individual’s preferences.
In terms of adoption, AI and ML will most likely impact competitive tier-1 and tier-2 operators with significant digital presences the most, and those that start early with a comprehensive strategy should reap meaningful rewards.
Individual smaller brand players with strong retail businesses are proving to be a bit behind but also should be able to garner significant value and differentiation from AI and ML.
SBCN: What are the reasons that the gaming industry has been slow to adopt these new technologies given all the proven benefits?
JA: This is a really important question, and one that differs from provider to provider, but there are some common themes.
First and foremost, is that up until recently, the majority of operators and platform providers simply did not believe or understand the value prop. Secondarily, even as organisations are starting to understand the value, they have a hard time prioritising implementation of AI, ML and personalisation strategies, over other items in their backlogs. Add to that that AI and ML is not a core area of expertise for most.
“…the industry is conditioned to buy proven products, not innovate around new technologies”
They may have data teams and they may use AI to run specific tasks, but this typically does not translate to doing anything at scale. We know this first hand as many of the companies we work for have large tech teams full of very smart people, that admit, they are challenged to implement AI and personalisation successfully, and come to us for help.
Lastly, the industry is conditioned to buy proven products, not innovate around new technologies. Companies want standardised offerings with proven ROIs and numerous scale use cases before making investments.
This is really hard to do with AI and personalisation as every customer’s needs and tech infrastructures are different. This creates a chicken and egg situation which ultimately leads to kicking the can down the road for many. However, we absolutely see that changing and are here to help facilitate it.
SBCN: What needs to happen for the industry to witness and maintain an upwards trajectory in correctly adopting and implementing such solutions?
JA: It’s all about prioritisation. Companies need to make this a key initiative for their business full stop, not because it’s a hot topic, but because AI and ML presents such a great and proven means of generating revenue, streamlining workflows and creating differentiation. That means dedicating budgets and resources and making sure it stays “above the line” year after year.
Additionally, companies need to look at AI and ML as part of their long term strategy moving forward. It’s not something that is going to be incremental to the business, nor is it a flash in the pan. It is a force multiplier and something that, if applied properly can be very strategic.
Finally, they need to recognise that they will need help along the way and that there are companies like ours, that have products, services and methodologies specifically focused on helping operators realise value and accelerate implementation, and that it is ok to admit that they need help.
SBCN: Could you offer some examples of where AI and ML can help and the opportunities that could be opened up?
JA: First, let me start by saying that I believe that AI and ML will fundamentally change the way gaming companies engage their customers, much like it did for music, tv and e-commerce.
“There are also huge opportunities to use AI to predict user behaviour and also help thwart unhealthy behaviours”
Perhaps the biggest area of opportunity is around personalisation of the user journey. This is pretty straight forward and it is about tailoring the experience and content in the sportsbook and casino offerings around the preferences of the end user. Again think Netflix and Spotify. With our customers we see anywhere between a 5% and 15% lift in GGR when the experience is personalised.
There are also huge opportunities to use AI to predict user behaviour and also help thwart unhealthy behaviours. So focusing on the areas of bonus abuse, risk and churn reduction. These are things AI models are very good at and things our customers ask for very frequently.
This is also a great place for operators to start, because they don’t require significant resource allocation, they are areas which typically rely heavily on legacy methodologies and processes. Streamlining these processes and increasing the fidelity around user behaviour can have a huge impact on the bottom line.
Finally, it is worth mentioning generative AI. Generative AI provides the opportunity to dramatically extend and enhance the conversation and dialog with the customer to create a more holistic entertainment experience.
Think about the concept of having your own personalised betting assistant who dynamically creates stories and provides stats and insights around events and games that you are interested in. Or an AI based problem gaming solution that helps predict and provide controls and support to make gaming safer.
SBCN: What are some of the major challenges that could be encountered through the utilisation of AI and ML? And how are these overcome?
JA: Time and the willingness to iterate. We have spoken to almost every major gaming operator about implementing AI in sections or pervasively across their business and some are willing to commit because they understand the impact the technology can make across their business, but many are not prepared.
To solve this challenge we have taken the majority of the heavy lifting away from the operator, and make it as easy as possible to harness the power of AI without causing disruptions in their roadmap or staffing plan.
SBCN: If a company was looking at making its first moves in adopting AI, what should a correct approach for adoption comprise?
JA: Have a commitment to create opportunities and solve business problems by harnessing the power of AI. Understand what technologies are available in the market that can be utilised.
Hire a partner that is going to work with you and listen to your challenges and help you solve or capitalise on an opportunity. Start small and be willing to learn and adjust to what your data is telling you to do. Integrating AI into an operator’s business can be done in stages, with great results.