What your AI can't do | Bridging the data capability gap

By Niall McKinney on 26-Apr-2019 15:15:23

AI is really sexy lately, with seemingly boundless power. Apparently, AI is going to do it better...whatever ‘it’ might be.

Because the truth is, many of the people who claim to be at the forefront of so-called artificial intelligence are actually doing data science, or, at best, machine learning. The claim on AI is misguided, and sometimes, even false. For all the allure of Data Scientists, Machine Learning, and AI, what do they really mean?

Like all great education providers, we have had great training. At “Data Science Unicorns and Silver Bullet AI” at SXSW, we heard from David Meza, Chief Knowledge Architect at NASA and got the following clarification from a literal rocket scientist:

  • The output of data science is analysis.
  • The output of machine learning is prediction.
  • The output of AI is action.

But let’s backtrack a little bit. You don’t have to work at NASA to know that AI stands for Artificial Intelligence. Customer service chatbots, algorithms, and even your doorbell could all be imbued with that not-quite-human quotient for intuition and protection. Knowing this, we can understand the secret sauce critical to creating great AI.

AI relies on data science and machine learning to predict what you need.

Data Science > Machine Learning > AI

What makes AI exciting is its ability to adapt with you, not just for you. Artificial Intelligence is dependent on your intelligence, taken from a variety of scientific tools, in order to make magic happen. Great AI means identifying the problems you can constructively solve. In the same way that AI keeps learning, you need to build an organization that keeps learning, to effectively deploy it and make sure it’s working well.  AI alone won’t solve your problems: it learns because you do.

To bridge the data capability gap to see real development, it has never been more important to re-skill teams so they can adopt with a changing world, rather than succumb to it. Build your company. Invest in your people. Think like your data, so you can enhance it with internet protocol.

If AI is adopting new skills, learning everything from your voice to your heartbeat, you have to take on the same mindset to keep up with the pace of change. Optimized data tools to create and allow for better decision-making, and clearer actions to see strong results.

Because while AI is deployed to solve specific problems, you need to know what those problems are to be sure AI is solving them in the most efficient way. AI is just one aspect of a workplace climate that keeps changing. Being ready to harness technology in new and exciting ways is the most important step for effective digitization. No matter the tools that come our way, it’s still a People First world.

It’s okay to be overwhelmed at first -many in leadership positions are. But not only is there potential for growth, such is essential on your journey to better business strategy. Just take it one step at a time.

Don’t be afraid to think bigger. The C-Suite will affect real change by leading by example, the organization has to take a full-service, all-hands-on-deck approach to adaptability. The quickest fixes are clear communication and enthusiasm, to grow all your resources most effectively.

Niall McKinney

Written by Niall McKinney

A successful leader in blue-chip companies, Niall is a VC-backed founder who built a multi-national digital transformation business to successful sale and exit, and holds extensive experience of leading digital transformation and organizational change. Niall is a keynote speaker on digital transformation, digital excellence and organizational agility. He has spoken at over 200 events including the Cannes Lions, Ad:tech, Advertising Week, and around the world on behalf of Google.

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