The topic of AI has reached such a fever pitch in the media with the coverage of driverless cars, conversational bots and even movies made by AI that it’s only a matter of time before every CEO starts asking their CIO “What’s our AI strategy”. For many CIOs this will be a “deer in the headlights” moment since the topic of AI is so multi-faceted it’s hard to know where to start. We put together this blog post as a primer for CIOs wanting to get to grips with the topic of AI.
This post is the first in a three part series. In this first post, we will give some insight and context into why your CEO is asking this question, why now, and why you. In the second post, we will give you a foundational framework to think about AI so you can give your CEO a thoughtful response. In the third and final post, we will discuss how you as CIO can engage the business on the topic of AI and important considerations when evaluating AI vendors.
CIO: “Why is my CEO asking me this?”
So why is the CEO asking you this now? CEOs are humans too and they react to their environment. Their environment is often dominated by other CEOs, their board and the outside world. AI as a topic has risen to the boardroom and the popular press with even Vanity Fair recently publishing an article titled “Suddenly Everyone is Obsessed with AI”. So if your CEO hasn’t broached the AI topic yet, they soon will.
As CIO you may be thinking why is this question directed at me? Why isn’t he asking the CFO, CTO, CMO, or COO? To answer that question we need to put AI in the historical context of the the role of the CIO.
The evolution of the CIO role
William Synnott, former Senior Vice President of the Bank of Boston, and William Gruber, former professor at the MIT Sloan School of Management, first formally defined the role of the CIO in 1981. They defined the CIO as the job title commonly given to the most senior executive in an enterprise responsible for the information technology and computer systems that support enterprise goals.
Up until about 2005 the CIO mandate was clear. Deploy the 6 or so key technologies to support the business: Accounting for Finance, Payroll & Benefits for HR, CRM for sales, Call centers for Support, Email and Security for all employees. The IT function collected the business requirements and then selected and delivered the application. It was very linear, typically took 12+ months and would only change every 5 years.
This new CIO role was not considered a glamorous or even mission-critical role initially. It was predominantly measured as a cost center and at one point the role was so unappreciated that the joke started circulating that CIO stood for “Career is Over”
Surfing the Waves
But like many executive roles, CIOs have had to evolve in response to their changing environment. For CIOs the biggest change in their environment was the nature of technology available to the enterprise. These changes would appear as waves to the IT function, starting from far away but gaining in power as they approached. Either CIOs had to learn to ride the wave, or be overpowered by the wave. Up until about 2005 there was just one wave, which was the transition from mainframes to client-server technology, but in the last 15 years the frequency and power of the waves has increased. A great CIO is like a great surfer. They can see the wave from far away and they can time how and when to ride it.
After 20+ years of calm, glassy sea the first big wave hit. Bigger and faster than anything a CIO had experienced previously. Drown or ride, those were your choices.
The first wave: On premise -> Cloud & Mobile & Social
Salesforce was the first cloud vendor to reach $1B in revenue in 2009 and paved the way for the mainstream adoption of cloud applications in the enterprise. Salesforce has since been joined in the “$1billion revenue” club for pure-play cloud applications companies by ServiceNow and Workday, The cloud wave was also amplified by the social and mobile technologies, which increased the volume of data shared across company boundaries.
This cloud wave profoundly changed the role of the CIO in two major ways. First, IT switched from being a capital cost to a variable operating cost where the premium was on speed and agility. This stressed the IT org that had been built for stability and governance. Second, the end user provisioning of cloud and BYOD mobile dynamic changed the balance of power. Previously, IT would tell employees what they would use. Now, employees choose what apps they want to use and bypass IT. Rather than deal with just 6-8 major business applications for the entire company, they now had to support at least a 10X increase in applications. As an example of the explosive growth just the Marketing function had 4,000 cloud applications available to them. The CIO had to develop new policies and frameworks to co-opt rather than ignore this trend.
Just as the CIOs were catching their breath, they got hit by a second wave.
The second wave: Small Data -> Big Data
The constant during the first wave was that IT’s primary responsibility was still enabling business processes. This forced IT to focus almost exclusively on the applications running underneath those business processes. As the concept of the data itself being valuable and needing managing hit the mainstream in 2011 with the McKinsey Global Institute publication of “Big data: The next frontier for innovation, competition, and productivity.” the role of the CIO changed once again.
CIO’s had to become familiar with the 5Vs (Volume, Velocity, Variety, Variability, and Veracity) of big data. They had to understand new storage and compute approaches such as MapReduce, Hadoop, Spark, and Cassandra. They had to build analytics capabilities to present the data to business owners. The scope of their world dramatically expanded.
This wave is still in motion. It hasn’t crashed on the shore yet. But on the horizon the beginnings of a third wave are emerging.
The third wave: unintelligent applications -> AI
During the explosion of the number of cloud applications being used inside an organization, these applications were still unintelligent. Namely, the application itself didn’t do anything unless a human took an action – responded to a support ticket, updated a sales opportunity – or maybe pre programmed a define rule to follow – such as nurture a lead based on the lead activities.
These applications were predominantly backward looking. They told you what had already happened. But with the collection of such big data sets from the previous wave, there was now a business imperative to glean more value from them. This meant one thing. Applications needed to become intelligent and predict what had not yet happened
The first examples of intelligence applications emerged in marketing and sales, with companies such as Quantcast doing predictive targeting and Everstring and Infer doing predictive lead scoring. But now we’re seeing AI start to emerge in fields as diverse as automotive, healthcare, and retail.
This growth in the volume of data and the need to capitalize on it has led to the concurrent growth of the role of data scientist. According to LinkedIn, there are now at least 180,000 data scientists in North America and the big 4 technology players – Amazon, Google, IBM and Microsoft – are actively targeting them with cloud machine learning offerings. Google’s CEO has stated they are now an AI-first (rather than mobile-first) company and Microsoft’s CEO has articulated 10 rules for AI.
So the waves are appearing on the horizon. It’s only a matter of time before they hit the enterprise. Now you know why the waves are appearing, what can you do to prepare? What’s the equivalent of learning to surf when it comes to AI?
Next week in the second post, we will give you a foundational framework to think about AI and how it relates to your business, so you can give your CEO a thoughtful response. As a teaser, here is everything you need to know:
AI = TD + ML + HITL
All will be revealed next week. Stay tuned!