AI First Strategy

So your organization is considering creating a “Cloud First” or “Mobile First” strategy and developing your industry’s next killer app.  Unfortunately, that paradigm alone will no longer differentiate your product or service offering. Instead, organizations need to be thinking about leveraging their vast quantities of data to create an “AI First” strategy. We define Artificial Intelligence (AI) First Strategy as follows:

The ability to leverage Machine Learning techniques, such as conditional probability computation, to automatically anticipate the next best action. This strategy can drastically improve the customer experience, drive efficiency, and optimize outcomes.

At its core, AI First Strategy involves data science and the ability to transform vast quantities of data into useful actionable insights. This ability to use various AI techniques such as machine learning, neural networks, and pattern recognition to gradually improve accuracy and “learn” from new data sets is nothing short of transformative.

Disappearing Devices

Amazingly enough, in the near future, our beloved devices will completely vanish and will be replaced by omnipresent AI.  This can seem a bit daunting, but not having to use a screen interface is the next big innovation. The goal of this technology is to deliver complete contextual relevancy to situations, do it automatically, and do it on a massive scale.  This ability to anticipate problems and customer needs can create tailored communications and situational awareness to achieve optimal outcomes.  AI’s contextual capability to delight customers and provides life-changing efficiencies is fast approaching.  It equates to delivering services at the right time instead of just in real time.

Some of the most innovative companies in the world are making considerable investments in AI to ensure we live in such a world within the next decade. Companies such as Google, Amazon, Apple, Facebook, and Baidu, to name a few, are placing massive bets on creating the tools of AI technology.  The new user experiences and efficiencies possible with this class of AI technology will disrupt markets and incumbents like never before.

AI Technology

As background, fundamental AI technology comes under the topic of data mining (discovering patterns) or generative (creating output based on a training set of data). Machine Learning particularly works on probabilistic algorithms such as belief networks, Bayesian networks, and probabilistic networks. Their usefulness comes from determining causality from large sets of data.

Machine learning technology is already having a significant impact on business today. Companies like Google are accelerating this trend by making development tools and advanced applications widely available to development communities on their platforms.  Technology such as Google’s language translator and photo services already allows developers to create customized applications that understand both speech and images quickly.  Novel new applications based on this technology are coming to market every day.

Another excellent example of AI building block technology is Google’s Knowledge Graph.  It contains more than 500 million objects and more than 3.5 billion facts about relationships between objects.  This data structure can be leveraged to create highly contextualized understanding by computers.  As additional computer-science and mathematical research makes AI algorithms increasingly sophisticated, vast amounts of other complex varieties of labeled data will be leveraged in exciting new ways.


All businesses must have an “AI First” digital strategy and roadmap to compete in the next decade.  If your organization is considering digitization and creating an AI-First Strategy, HBSC can help.  Please contact us at or call us at 800-970-7995.

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