Big Data and AI technologies have the promise to transform entire industries and provide new competitive advantage. Many companies claim that they are using AI but in very few companies it is playing a strategic role. (See Exhibit 1.)
Artificial Intelligence (AI) has been around for decades. In fact, I published a research paper in 1979 in I.E.E.E. Transactions on Pattern Analysis and Machine Intelligence. However, it is only in the last few years that it has reached an inflexion point where storage capacity and databases required for Big Data, computing power required for massively parallel computing, and AI algorithms have reached an inflexion point for it to be commercially viable.
AI is exactly where Cloud Computing was 10 years ago, lots of hype but very little strategic impact. Current uses of AI are in automation areas such as chatbots, voice recognition and response, personal assistants, diagnosis, and recommendation engines. However, use of AI for business transformation is about to explode. AI market worldwide will reach $60 Billion in 2025 from $1.4 Billion in 2016 (See Exhibit 2.)
Strategic business use cases for AI are those related to improved data-driven decision making. These include market insights for mergers and acquisition, competitive analysis, developing proposals for large projects, and ensuring effective procurement strategies.
Businesses are spending $15 Billion annually on external data but unfortunately only 0.5% of external data is being utilized in decision making (Source: J.P. Morgan Alternative Data Altering Investment Landscape). Leveraging Big Data and AI Technologies makes this possible leading to significantly improved decision-making. (See Exhibit 3)
What is different is not only the volume and sources of data but more importantly types of data. (See Exhibit 4.) Making sense of unstructured data is not possible without the aid of AI.
This unstructured data needs to be curated before it can be analyzed and the techniques for doing so require machine learning and deep learning. Also, what is critical for decision making is combining both internal and external data for improved decision making.
Digitization is different than Digitalization or Digital Transformation. This is to empower employees to make faster and smarter decisions. The CEO needs to be the champion as this is a business transformation and needs to get business heads involved to drive the change. This is not a technology transformation and should not be relegated to IT departments. This is very different than Cloud Computing which was much more IT driven.
According to a 2017 Deloitte Survey, when executives familiar with AI were asked regarding its business benefits, most responded with better products, operations, and better decisions as opposed to headcount reduction through automation. (See Exhibit 5.) This is supported by an IBM Survey that shows 74% of executives believe that AI will change how customers view their brands but only 41% of them say they have an AI strategy.
Many CEOs who have realized the importance of AI are held back because of the fear of implementation failure. Some of them believe this requires large investments and/or large year-long consulting projects with uncertain outcomes. Others are held back because they believe resources required such as Data Engineers and Data Scientists with domain understanding are necessary for successful implementation and are difficult to find. This is far from truth. Fortunately, AI and Big Data technologies have come to prominence at the same time as Software-as-a-Service (SaaS)
model. Too many enterprise AI projects have failed due to a lack of understanding of this new model. Under this paradigm, risk is significantly reduced as there are many companies offering industry specific solutions which can be implemented in a few weeks instead of months. Also, it does not require deployment of large investments as the SaaS model does not require up-front payments and can be closely tied to value realization. The reason SaaS solutions are less risky and quicker to implement as most of the heavy lifting in terms of solution development has already been done by the vendor. (See Exhibit 6)
So, what does the CEO need to do? Like all transformational changes, AI has cultural and organizational impact. The most important responsibility CEO has in setting an AI strategy is aligning the organization. CEO needs to develop, communicate, and secure commitment of the C-suite executives to the long-term strategic vision for AI tied to business strategy and execution.
Once this is done, he/she needs to rely on the business heads to undertake AI initiatives in their own domain in support of the strategic vision. Business heads then can identify and prioritize in their own areas AI applications that would be most beneficial to increasing top line revenue, improving customer and employee satisfaction. These initiatives chosen should be understandable and designed to augment human capabilities by making employees more productive while improving decision-making. The specific initiatives themselves should be small and implementable within a few months. Business heads need to identify Use Cases which would be most beneficial to their group and get their buy-in.
They can then assign a team to research and find suitable SaaS offerings which is a good match for their Use Case. AI does require training the system and the efficacy will improve over time. Attention also needs to be placed on workflow integration. Organization adoption is key so the rollout needs to be carefully coordinated and reward systems changed to match the new business processes. Most of this requires normal business related project management and not deep understanding of AI/Big Data technologies. The vendor is providing the industry specific solution and any data science expertise needed! (See Exhibit 7)
While there has been many technology revolutions-- Mainframe, Server, Personal Computers, Internet, and Mobility -- I believe AI will be the most transformative technology we have ever experienced as it will fundamentally improve business decision-making. The stakes are high! AI has become a strategic imperative for the CEO to understand and own. Call to all CEOs: Become the champion of AI strategy for the company!
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