Successful AI Projects Seek A Spectrum Of Outcomes

As artificial intelligence (AI) continues to move from the summer of hype to the fall tech conference news cycle, mass confusion has begun on what AI can be used for. From fears of SKYNET, to hopes for the computer in StarTrek and Jarvis in Iron Man, the value will come from defining the proper outcomes. AI is more than just a fad. With a market size of $100B by 2025, Constellation sees the AI subsets of machine learning, deep learning, natural language processing, and cognitive computing taking the market by storm (see Figure 1).

FIGURE 1. ARTIFICIAL INTELLIGENCE MARKET WILL SURPASS $100B BY 2025

The disruptive nature of AI comes from the speed, precision, and capacity of augmenting humanity. When AI is defined through seven outcomes, the business value of AI projects gain meaning and can easily show business value through a spectrum of outcomes (see Figure 2):

1. Perception describes what’s happening now. The first set of outcomes rudimentary describe surroundings as manually programmed.
2. Notification tells you what you asked to know. Notifications through alerts, workflows, reminders, and other signals help deliver additional information through manual input and learning.
3. Suggestion recommends action. Suggestions build on the past behaviors and modify over time based on weighted attributes, decision management, and machine learning.
4. Automation repeats what you always want. Automation enables leverage as machine learning matures over time and tuning.
5. Prediction informs you what to expect. Prediction starts to build on deep learning and neural networks to anticipate and test for behaviors.
6. Prevention helps you avoid bad outcomes. Prevention applies cognitive reckoning to identify potential threats.
7. Situational awareness tells you what you need to know right now. Situational awareness comes close to mimicking human capabilities in decision making.

FIGURE 2. SPECTRUM OF SEVEN OUTCOMES FOR AI

The Bottom Line: Form Follows Function In AI Powered Approaches

AI driven smart services will power the future business models. As with most disruptive business models, form must follow function. Just enabling AI for AI’s sake will result in a waste of time. However, applying a spectrum of outcomes to transform the business models of AI powered organizations will indeed result in a disruptive business model and successful digital transformation.