Is it Too Late for Your Business to Win the Race to AI?

Artificial intelligence feels like it’s in the middle of an arms race — in the boardroom at least.

Atif Kureishy
Atif Kureishy
2017년 12월 18일 3 최소 읽기

Artificial intelligence feels like it’s in the middle of an arms race — in the boardroom at least.

Over the last few months, nearly every executive I’ve talked to, be it in banking, telco, manufacturing or many other industries, has talked up AI, machine learning and deep learning as “must-have” technologies. And while Teradata’s latest AI report reveals that 80 percent of enterprises have invested in AI, from my experience, not many of these businesses feel like they have AI down pat.

Gartner has commented that “AI washing” is muddying the benefits of AI — making everyone feel like they have adopted it but proliferating confusion about its actual benefits.

The reality is, for any enterprise seeking AI dominance, it’s less about the technologies they buy today than it is about the foundation they’ve built up till now. It’s a tough balance to strike: It will be very difficult for any business to leapfrog over AI’s fundamentals — a strong data science foundation with advanced analytics capabilities. But at the same time, businesses can’t take long to play catch-up.

The good news is, competitors haven’t figured out how to turn AI into a silver bullet either. So while the race is certainly on, there are no clear winners just yet.

Michele Goetz of Forrester says, “While many of the rules for business competitiveness and survival had already been redefined before AI became broadly available, its emergence as a viable capability has brought markets and businesses to a tipping point as the next cycle of technology disruption begins in earnest.” It is clearly a business differentiator that is rapidly going from sought-after asset to mature technology.

However, the larger an organization is, the more complex it is. These organizations likely have more fragmentation, a larger proliferation of bad data science practices and have a higher exposure to disruption. This is a double-edged sword. Complexity is difficult to overcome, but complex organizations also have more areas that AI can transform.

The hype around AI is so fervent that enterprises have assigned it this “winner takes all” stature. But it’s not hard to see why this has businesses laser focused on adopting the technology. It takes a very short-term memory to realize what Amazon has done to retail in the last few years. Even the most established giants of that industry are feeling the heat of competition. The reality is enterprises today feel they either have to be a threat or be threatened. They see AI as an opportunity they can’t miss.

The good news is, competitors haven’t figured out how to turn AI into a silver bullet either. So while the race is certainly on, there are no clear winners just yet. The challenge is the agility to change. And even the businesses right now that have the most agility are struggling in that sense.  

Jeff Bezos likes to call Amazon a “Day One” company — always in startup mode, always ready to change. And in fact, not adopting AI is something that Bezos believes threatens to turn companies into “Day Two” organizations. At the same time, Amazon isn’t known for its employees’ long tenures. The rate of change necessary to succeed to customers at these companies is in other ways potentially the source of internal friction. We are truly witnessing some sort of terminal velocity point for rate of change, and if a business can live up to both internal and external pressures, it could come out on top in the AI revolution.

All this promise and opportunity, combined with the need to pivot fast, is creating a lot of tension surrounding AI adoption. And the only way to not get caught up in the drama is to have those foundational elements that ensure your business is data-driven in the first place. If you aren’t there now, it’s time to get there right now. It’s time to let go of any technological debt your company has invested in. You need an architecture that allows you to deliver on today and predict tomorrow. You need to be ready to embrace new approaches, and you have to remain competitive. To do anything else is to risk irrelevancy.

Want to measure your progress with AI against other enterprises? Read our recent State of Artificial Intelligence for Enterprises global report, where business, in multiple industries, get granular about what they’re doing with AI technologies.



약 Atif Kureishy

Atif is the Global VP, Emerging Practices, Artificial Intelligence & Deep Learning at Teradata.

Based in San Diego, Atif specializes in enabling clients across all major industry verticals, through strategic partnerships, to deliver complex analytical solutions built on machine and deep learning. His teams are trusted advisors to the world’s most innovative companies to develop next-generation capabilities for strategic data-driven outcomes in the areas of artificial intelligence, deep learning & data science.

Atif has more than 18 years in strategic and technology consulting, working with senior executive clients. During this time, he has both written extensively and advised organizations on numerous topics, ranging from improving the digital customer experience to multi-national data analytics programs for smarter cities, cyber network defense for critical infrastructure protection, financial crime analytics for tracking illicit funds flow, and the use of smart data to enable analytic-driven value generation for energy & natural resource operational efficiencies.

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