Dan Elron is Managing Director, Corporate Strategy, Innovation and Technology at Accenture, and leads many of the global management consulting and professional services firm’s innovation initiatives. Elron, a speaker at Transform.ai, a June 15–16 Paris conference on artificial intelligence, recently spoke to The Innovator about how AI will transform traditional companies.
Q: At the Transform.ai conference in Paris there was talk about how artificial intelligence represents a chance for traditional companies to regain control of their destiny and have direct access to their customers again. Do you agree that AI will transform the customer relationship?
DE: Yes, AI will transform how and what the customer purchases, it will transform the architecture of companies, their business processes and how each company interact with its ecosystem. We are in the early stages;he number of large companies that have deployed AI on a large scale is still small. But eventually AI solutions can solve many problems, allowing companies to constantly learn and act on experiments; AI can take away structured one-size-fits-all business models, creating much more adaptive enterprises.
Q: What is the biggest value AI brings to an organization?
DE: Many people say the biggest value of AI is predicting what is likely to happen; if you can do that, you can optimize your supply chain, operations, advertising, etc. For many companies AI’s effects will initially only be felt in pockets of the organization. AI-enabled processes that span across companies — complete end-to-end services — generally still are three to five years away.
Q: Won’t it be hard for traditional companies to compete with new ones that have been built from scratch using AI in every part of their business? How realistic is it to think, for example, that a traditional bank could suddenly be as tech-savvy and agile as China’s Ant Financial?
DE: It is true that competing with new players can be challenging, but we should not under- estimate the core of traditional companies; it can be very hard to replicate. For example, in the insurance business, when it comes to selling an insurance policy, the customer connection could occur on an app or online and digitally native companies may do this better — but we have not seen new players who can perform underwriting or other core functions of the insurance sector. We are likely to see a fragmentation of the business, with digitally native, customer-focused companies helping with the front end, and traditional companies delivering the core products. As for banks, I disagree that banks are necessarily at a disadvantage. Some banks are replacing all of their systems, moving completely to the cloud and using open, micro-service architectures that help them to become flexible platforms and plug-in diverse, innovative solutions. Goldman Sachs is a great example of a traditional company that has decided that they will deliver transaction enablement. They expect other players to develop new trading algorithms, using some of Goldman’s data and its platform.
It is important not to underestimate what traditional companies do well and also not to underestimate the impact of regulation in the Western world. This helps incumbents and gives them time to adapt, clean up their data and develop sophisticated AI solutions. The percentage of fintechs which have scaled is low, and many will succeed through collaboration with incumbents.
Q: What is the best, most efficient way, for companies to leverage AI to stay competitive?
DE: Companies need to decide whether they want to become a platform play or operate on someone else’s platform. While it is too early in some industries to decide, all companies will have to make a conscious decision soon, because in any particular sector there is room for only so many platforms. What is clear is that you have to start developing AI muscles today. Companies should have already started understanding what data they have, annotating and enhancing it, and building data-driven processes and a data-centric culture. Our vision of AI in such organizations is as an augmenter for many jobs, that enhances the quality, richness and impact of the work.
Q: What is your best advice for companies struggling to simultaneously adopt a host of new technologies, realign their workforce in the age of AI, and rethink the way they are managed?
DE: Look at the auto industry. There has been a surge of innovation in that industry that is challenging the sector’s fundamental business model. Auto manufacturers have to transform their value proposition , and thus we see them becoming much more edgy. They have had to stand back and ask themselves ‘Are you a car company or a transportation company?’ Many young people are not even bothering to get drivers’ license; their generation is likely to use autonomous car sharing services. So one question is what kind of car will automakers need to build? Car sharing services may use cars 70% to 80% of the time, versus today’s cars that are used 5% of the time. So cars have to last much longer and be more reliable, in addition to driving themselves. It is exciting for engineers to develop cars that can run for many more hours and miles. This is the kind of challenge that keeps employees motivated, and AI can now help them in applying creativity and innovation to these new problems. Every industry will have to understand how customer demand will change, and AI will help them do that and reduce the need for guesses about the future. But keep in mind that AI is a tool kit — a very broad tool kit. Every day we see solutions available that are pretty good. That is good news. But it is not the tools that are going to make the difference — it is the way companies will use them.
Q: Becoming innovative is not just about technology. It is about the way the company it is managed and the way it thinks about its products and customer service. Often the innovation sits at the edges but does not infuse the core. What’s the best approach to avoiding that scenario?
DE: Both “innovation” and “digital” should be seen as adjectives and not nouns- they are not destinations by themselves. Initiatives around innovation and digital have to be attached to significant business objectives. They can help transform and scale the core business, help enter and scale new businesses and help companies make a smart pivot at the right time — that is how we see innovation driving success. Senior management thus needs to have an innovation agenda aligned to these four specific dimensions of change. If, for example, they want innovation to transform the customer experience ,a really excellent goal,– this may require transforming the supply chain and building a partner ecosystem to help provide a much better experience. This broad approach encourages middle management, which often resists change, to engage in the innovation projects;it makes it much more compelling if they see a clear destination, and that brings innovation to the fore across the company.
Accenture’s Innovation Architecture is designed to help traditional companies actually scale innovation. Among other things, we help our clients start with applied R &D, move to ideation and prototyping, use design studios that can help build experiences and products, and leverage delivery centers that can help scale new products and services globally.
When approaching innovation, CEOs need to think about five things: strategic relevance and alignment; leading from the business problem, not from the technology; externalization, i.e. making sure your approach is something you do within an ecosystem; creating a set of metrics adapted to the risk profile of innovation, in other words don’t penalize failure; snd finally , because the culture and incentives at many traditional companies work against scaling innovation, there is a need for role models. A CEO intent on innovation needs to both understand the value of AI and be personally committed to and engaged in its implementation.