What to Expect in 2020: Greg Betz Answers Five Key Questions Around Data, Intelligence and Automation

In a candid tete-a-tete with NTT DATA, Greg Betz, senior vice president at NTT DATA Services, discusses technology trends in data, automation and AI. For the year ahead, Greg answers five pertinent questions concerning what companies can expect, and how they should prepare themselves to compete in the brave new world of AI.

Q: Name one must-have for companies to be successful in the near future.
A: Data. Data. Data. Data is already the most sought-after currency in the new world order — the AI-driven world. Enterprises can no longer put it on the back burner because without integrated and relatively clean data, none of your “intelligence” or automation is going to work. Enterprises need to be data-ready and they need to review data quality and their architecture to make sure it’s optimized for maximum automation impact. If they delay it longer, enterprises may be left behind while their competitors will have moved on into the next phase of the AI and automation journey.

Q: Which technologies will see strong adoption this year?
A: Continued expansion in RPA. RPA has seen robust adoption over the past few years and we will see broader adoption in industries such as Healthcare, Banking and Insurance. RPA adoption will be more significant in situations involving complex, costly, or legacy IT — where there is no built-in functionality to automate. There will also be more “native” automation and integration functionality in Salesforce, SAP, and other software packages.

2020 will also bring in continued experimentation and more Proof of Concepts (POC) to use AI for greater Return on Investment (ROI). This also means IT and business leaders teaming up to drive the scale needed to deliver on this ROI.

Q: What should enterprises guard themselves against?
A: Not doing their due diligence. I see enterprises continue to struggle with the ability to scale automation because they have not done their due diligence. They glossed over the key steps of standardizing and optimizing process before (or during) the deployment of automation. Going back to my earlier point of data — companies should absolutely focus on having the right data and having all their ducks in a row before taking the plunge. Otherwise, it will be difficult to reach efficiency, scale, and effectiveness goals.

Q: What challenges lie ahead for enterprises afoot on their automation journey?
A: AI transparency. For those that begin to deploy their AI solutions, AI transparency will be their next hurdle to cross. Sooner or later, executives will have to truly understand the core algorithms that run their enterprises and iron out all the possible kinks. They will need to set standards and governance processes and co-opt data scientists and engineers who built and trained the automation models, so everyone is on the same page or run the risk of adverse ramifications.

Q: What new technology developments can we expect in 2020?
A: Auto Machine Learning, or AutoML. Data cleansing. Data privacy. I would definitely expect to see more and more AutoML solutions in the market, especially since we have a scarcity of data scientists (And they are expensive too!). And the enterprise will need to move quickly in their AI adoption. Going back to my first point — we will also see more sophisticated, commercialized solutions for data, whether it’s for cleansing, integrating or optimizing. And along with that, we will also have more regulations that empower data privacy and controls, making enterprises more accountable for the data they store, consume and distribute.

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