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The robots are here – and they want to help. In the recently released 2019 Deloitte Global Human Capital trends report, while 80 per cent of the 10,000 executive respondents indicated that they expect the use of cognitive and AI to increase over the next three years, only 13 per cent believe that automation will dramatically reduce jobs.

But Deloitte’s research tells us that we still have a lot of preparing to do: Only 26 per cent of respondents said they are ready to address the effects of AI and other automation. So, where should we start?

Get your house in order

A recent whitepaper published by Cindy Gordon, chief executive at SalesChoice Inc. – an award-winning AI, cognitive sciences and advanced analytics company – in partnership with the Bedford Group, titled Staying Relevant – What Every C-Suite Leader must know about AI Readiness outlines an AI framework to guide your AI journey. Here are a few key points noted by Dr. Gordon:

Start with the business problem:

AI is a discipline needing governance, strategy, structure and cross-functional and collaborative leadership. It provides powerful tools that can help organizations propel forward, leapfrogging competitors, if rooted in a clear business strategy and strategic problem. However, without this link and focused discipline, companies are in jeopardy of chasing the bright shiny object, which is costly and unproductive.

Garbage in, garbage out:

AI is only as good as the data and feedback it receives. If we feed it biased and incomplete data, insights are flawed and less reliable. Thus, organizations need to first get their data “house” in order before embarking on a more robust AI journey.

Patience is key:

AI learns over time, just like humans. While 68 per cent of larger organizations in Canada have adopted AI in some form according to a recent study What’s Next in AI? (Forbes Insights, 2019), it is important to make clear that AI implementation is a long game. Unlike technology “pilots” to which we are accustomed, AI is a longer-term strategy from which you may not see optimal results for a decade or more.

Prepare your workforce

New jobs and “superjobs”

Stephen Thomas, director of the Smith Master of Management Analytics & Smith Master of Management in Artificial Intelligence says in his article Assemble The AI Dream Team that “it takes an AI village” (and not only data scientists) to properly implement and manage AI. Mr. Thomas identifies as many as eight relatively new and emerging roles – requiring skills that are in great shortage – from data engineer to client solutions specialist.

And it’s not just net new jobs that will emerge. One of the trends identified in the Deloitte report is the emergence of “superjobs." As automation frees up capacity for our human workers, we will have the opportunity to explore combinations of unlikely jobs into “superjobs” to drive more impact. For example, as some of investment advisers’ core tasks are automated by robo-advisers, capacity is freed up for human advisers to serve as career/life coaches – this would enable them to get to know clients’ ambitions and aspirations and make more informed investment decisions.

Focus on building human and digital/technology literacy skills

As automation gets smarter and takes on more tasks, we will need to up our game in skills such as curiosity, critical thinking, advanced analytics, user-centred design, mathematics and statistics. As well, root causal analysis will become more and more important across functions and levels. Also, while not everyone will be expected to have coding skills, we will all need a basic level of digital literacy and a foundational understanding of AI basics and considerations (e.g., leveraging data as a strategic asset, differentiating transparent versus black box AI, solving ethical dilemmas, etc.).

Start them young

Some countries are already embedding AI and other technology-relevant topics into curricula as early as elementary school. In Canada, some corporations are taking the lead and launching innovative programs in partnership with schools, from which they then have access to future job-ready talent. For example, through its Pathways in Technology Early College High Schools (P-TECH), IBM partners with schools and governments to equip high-school students with future-ready skills. IBM’s Skills Academy provides online training for university students, offering skills in mobile, AI, cybersecurity, analytics and cloud computing technologies.

For both our current and future workforce, a commitment to lifelong learning will be critical to optimizing the power of our newest members of the worker ecosystem – let’s help them help us.

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