Has AI become a Utility Function?

It’s hard to miss all the attention and hype Artificial Intelligence (AI) is getting these days. Everywhere you turn there are articles on a myriad of AI related topics such as deep learning, machine learning, cognitive computing, computer vision, natural language processing (NLP), etc. Frequently these terms are used interchangeable despite meaning very different things – a sign that many people still don’t understand this field. Every conference or event is now an “AI Summit”. All start-ups are now “AI based”. Analysts publish new AI statistics every day that further fuel the hype.

Have we reached an all-time high AI saturation point? What happens if AI doesn’t live up to all this hype?

Or maybe something else happened. Is it possible that all businesses are really now becoming AI powered businesses? And if so, how did this happen?

 

AI is everywhere

The reality is AI is now everywhere. Is some ways, it’s been a logical progression. The era of big data and cloud has finally converged to drive a significant paradigm shift that has enabled AI to become practical and accessible to both consumers and businesses. The volumes of data that continue to be collected now have purpose in training sophisticated deep learning models. The cloud provides access to scalable, parallel processing at low cost which is enabling cloud vendors to create machine learning algorithms and deploy in an AIaaS model.

Businesses can now unleash powerful machine learning and data science technologies that turn data into game-changing insight. AI is being used in a variety of ways in the enterprise. Predictive analytics, machine learning, and natural language processing (NLP) are the most widely used AI-powered solutions, followed by voice recognition and response, virtual personal assistants/chatbots and recommendation engines.

AI is rapidly becoming a utility function much like electricity and water.

I challenge you to do something today that does not leverage AI and machine learning. Checked your email lately? Spam filters are one of the earliest uses of AI. Watching your favorite show on Netflix, Hulu or Amazon Video? Machine learning powers their recommendation engines. Speaking to your Siri, Alexa, Cortana assistant? That’s NLP translating your voice to action. Driving your car and using Waze or Google Maps? Machine learning algorithms are used to analyze real time traffic data to suggest the best routes. Using a ride sharing app like Uber or Lyft? Machine learning is used to determine wait time and pricing. Do you use a financial platform like Betterment or Wealthfront? The robo-advisor algorithms automatically rebalance portfolios to increase returns. Getting fraud alerts on your mobile phone? Most likely a machine learning algorithm detected a unusual spending pattern.

The understanding that AI is here and now is still elusive to many that believe it’s still science fiction. Consumers use more AI than they realize. While only 34% think they use AI-enabled technology, 84% actually use an AI-powered service or device.

 

Investments in AI at all time high

It’s not surprising AI is so pervasive if you look at the amount of investment businesses are making in research, products and initiatives.

The FAMGA stocks (Facebook, Apple, Microsoft, Google and Amazon, whose collective market cap is $2.7 trillion and have become a bellwether of tech trends) are all pouring big investments in AI, expecting it will fuel their next wave of growth. They are also re-structuring their product development and go to market efforts to better prioritize AI related opportunities. They have collectively invested over $8.9 billion in AI related acquisitions.

Amazon has fully re-organized itself around its AI and machine learning efforts. Amazon uses a “flywheel” approach that ensures that AI innovation in one area of the company is leveraged throughout the entire organization.

Google invested up to $30 billion in AI with 90% on R&D efforts and 10% on AI acquisitions. Machine learning is getting up to 60% of that investment. And this is all forward looking as this represents a 3x investment as compared to the current growth of the AI industry.

As part of its re-invention strategy, Microsoft has been investing big time in future technologies like AI. They setup an Artificial Intelligence and Research Group back in 2016 that now has more than 8,000 computer scientists and engineers. The most recent shift came this year, when Nadella announced a restructuring of the company so it can give AI even more of a focus.

 

Start-ups fueling the AI revolution

It’s not just the large established players that are driving innovation velocity around AI. New AI start-ups are appearing every day.

Global investments in AI startups increased 150% this past year and there is a global shift occurring in AI investments. Chinese AI startups raised $5B in VC funding last year outpacing the US. The Chinese government is focused on becoming the world’s leading AI innovation center by 2030.

Deep learning applications and platforms continue to garnish the largest investments.

There are many companies pioneering the shift to AI. Companies like H2O.ai are democratizing AI by creating an open source machine learning platform that is accessible to everyone. Fractal Analytics uses AI to power decision making for Fortune 500 firms combining data science and behavioral science to facilitate decisions. DataRobot is an enterprise machine learning platform designed for broad adoption and usability across the many skill levels in an organization. CrowdAI is fascinating startup that captures images of the world everyday and turns them into meaningful insights.

And there are companies like NVIDIA that have re-invented themselves to become foundational AI players by applying their strengths in the GPU market to AI learning by processing millions of mathematical operations in parallel.
This level of innovation in AI has created a major inflection point that is triggering massive acceleration not just business innovation but human innovation.

 

Businesses adopting AI to drive growth

While AI is increasingly prevalent in our consumer lives, businesses are still in the early innings of launching real programs rooted in AI. The market potential is huge with Gartner estimating that $3.9 trillion in AI-derived business value will be created by 2022.

We are starting to see progress. According to Narrative Science, 61% of businesses have already implemented some form of AI. AI is creating the need for executive roles similar to Chief Digital Officers (CDO) that were created when digital transformation was the big craze. 62% of companies now plan to hire a Chief AI Officer.

Many industries are now seeing tangible benefits from the application of AI.

State Farm is investigating if computer vision to detect distracted drivers using a mobile app or OnStar to track driving patterns to then provide discounts for safe driving habits. It’s clear that collecting and interpreting driver data will play an increasingly important role in customizing insurance options and providing customer discounts.

Allstate has created a virtual AI assistant called ABIe to assist its sales agents in providing quotes and answer questions for its newly created commercial insurance business. Previously agents were trained in selling personal insurance products and the shift to commercial products had a steep learning curve and resulted in their sales support center getting flooded with inquiries. The additional of this virtual sales agent has reduced lost business and is no processing 25,000 inquiries per month.

Franklin Templeton used machine learning to generate $600m in new assets leveraging a Fractal Analytics Customer Genomics to create probabilistic scoring on the propensity to buy and react to certain products. This helped Financial Advisors (FA’s) to communicate information about products at the right time, through the right channel to increase effectiveness resulting in a 26% sales lift and 1300 incremental leads. They now have an adaptive customer intelligence platform to build on in the future.

 

Is your business falling behind?

While there are many examples of businesses adopting AI for certain use cases, these businesses are not fundamentally changing the way they do business. Incremental change is unlikely to deliver the needed results.

The ultimate question for any business is are you falling behind in AI? Are you leveraging AI to make a fundamental shift?

Let’s consider the lending market. While many financial institutions are investing in AI for their lending products, FinTech lenders, for which the origination process takes place nearly entirely online, and leverages sophisticated machine learning algorithms to accelerate approval decisions, have grown from roughly 4% market share in 2007 to 13% market share in 2015 and are now estimated to have 30% market share.

These examples exist across all industries – AI powered start-ups waiting to disrupt.

If your business is not fundamentally based on AI in the next couple of years, you may no longer be in business.

 

The article was originally published on Forbes and is reposted here by permission.

Frank Palermo

Executive Vice President - Global Digital Solutions, Virtusa. Frank Palermo brings more than 24 years of experience in technology leadership across a wide variety of technical products and platforms. Frank has a wealth of experience in leading global teams in large scale, transformational application and product development programs. In his current role at Virtusa, Frank heads the Global Technical Solutions Group which contains many of Virtusa’s specialized technical competency areas such as Business Process Management (BPM), Enterprise Content Management (ECM) and Data Warehousing and Business Intelligence (DWBI). The group is responsible for creating an overall go-to-market strategy, developing technical competencies and standards, and delivering IP based Solutions for each of these practice areas. Frank also leads an emerging technology group that is responsible for incubating new solutions in areas such as mobile computing, social solutions and cloud computing. Frank is also responsible for overseeing all of the Partner Channels as well as Analyst Relations for the firm. Prior to joining Virtusa, Frank was Chief Technology Officer (CTO) for Decorwalla, an emerging B2B marketplace in the interior design industry, where he was responsible for the overall technology strategy, creative direction, and site development and deployment. Prior to that, Frank was CTO and VP of Engineering for INSCI Corporation, a supplier of digital document repositories and integrated output management products and services. Prior to INSCI, Frank worked at IBM in the Advanced Workstations Division, and took part in the PowerPC consortium with IBM, Motorola and Apple. He was also involved in the design of the PowerPC family of microprocessors as well as architecting and developing a massive distributed client/server design automation and simulation system involving thousands of high-end clustered servers. Frank received several patents for his work in the area of microprocessor design and distributed client/server computing. Frank holds a BSEE degree from Northeastern University and completed advanced studies at the University of Texas.

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