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Artificial intelligence: The king of disruptors
SAS CIO Keith Collins discusses how to help IT teams prepare for, and benefit from, artificial intelligence tools
I’m a fan of futurist Ray Kurzweil. He predicts computers will have human-level intelligence by 2029, and that by 2045 computers will surpass human intelligence.
He and I agree that artificial intelligence is a positive force to augment human capacity. Like eye glasses and hearing aids, we will come to see AI as an extension of the human experience. AI may be the biggest disruptor society has ever experienced. But it’s not just a disruptor; AI is also an accelerant with the potential to enrich human learning, discovery, and productivity personally and professionally.
Put AI in perspective as a societal disruptor
A few years ago, we reached the point where available data exceeded a human’s capacity to process and understand it. Think about it from a historical perspective. In the 1400's, the printing press lowered the cost of disseminating information a thousand-fold. This flood of information sharing marked a major societal disruption.
Fast forward to the 20th century when the Internet was introduced. Information sharing increased from printing press standards by a factor of 10, and the world was disrupted again.
[ Read also: Artificial intelligence: 4 truths CIOs should know. ]
AI represents the next frontier in technological and societal disruption. Even though there’s currently a lot of hype surrounding AI, it’s important to consider the many ways AI can transform your enterprise so you ride the disruption wave instead of drowning in it.
Why AI now?
AI has been around for decades. The science isn’t new. So why all the hubbub now? The answer is convergence.
Computing power is up, while computing costs are down. In the early 1960's, for example, a gigaflop cost approximately $153 billion in today’s money. But now, a gigaflop of computing power costs about 3 cents. Plus, the increasing popularity of GPUs provide affordable, energy-efficient computational speed on top of it.
Add to that affordable data storage. Storing a gigabyte of data in the 1960's cost more than $1 billion by today’s standards. Now a gigabyte of storage costs around 2 cents. That’s good news because the advent of the Internet of Things and streaming data means we’re rapidly heading into the land of zettabytes. That massive amount of data can lead to building deep neural networks to train and retrain algorithms, essential for data-hungry AI.
Decades ago, we fantasized about making AI part of everyday life, but we couldn’t afford the technology underpinning it. Now we can. Let the disruption begin.
Apply AI to your enterprise
If you’re part of the IT organization, you’re already in a great position to help your enterprise thrive in the face of disruption – especially if you already possess predictive modeling, forecasting, and optimization skills. The critical skills for AI success likely reside in your IT wheelhouse, so let your geek flag fly.
Your sensibility is an essential voice in the conversation that could reframe your entire enterprise if you’re willing to open the door to the “art of the possible” AI represents.
So how do you put AI into action to realize what’s possible? You need to:
- Understand the business in depth so you can articulate the opportunity in the terms your enterprise uses. Connecting the value of AI in context is more than half the battle. Understanding the technical issues to operationalize AI outcomes represents the other half. The discovery may be easy, but automating operations, monitoring outcomes, and protecting the customer and the enterprise must also be managed.
- Understand technology advancements and how they can improve your business. Participate in conversations about emerging technologies across a variety of industries, and figure out what you can borrow and apply to your own organization. Just like converging technologies are accelerating AI, the same can be said about the diversity of innovations coming from other businesses that could enable disruption in your own.
- Examine your software portfolio. Analytics software has been around for four decades. You probably already have some that can be leveraged on your AI journey, allowing you to experiment without new investment dollars. It’s important to understand that classic predictive analytics acts as the primary solution for many problems being cast as AI today.
- Make the connection between what you’re learning and how it applies to your enterprise so you ask the right questions. Think about the bigger picture regarding how technology advancements can be applied in new ways. By design, IT colleagues are the plumbers who get called when the sink is clogged. The good news is you know how all the plumbing fits together. With a targeted approach of building AI technology skills and connecting them to existing business challenges, you can add “architect” and “builder” as new career badges.
Our COO likes to say, “Data without analytics is value not yet realized.” With all the AI hype others might say, “Data without AI is value not yet realized.” Either way, the objective and the journey is one in the same. With that idea in mind, I urge you to not wait. Be bold and start the conversation. Lead the journey.
[ How do you stack up to digital transformation leaders? Read our new report from HBR Analytic Services: Transformation Masters: The New Rules of CIO Leadership. ]