In Review: A Chief Data Officer’s Guide to AI Strategy

In 2017, leading global research and advisory firm, Gartner, Inc. published a groundbreaking paper (A Chief Data Officer’s Guide to AI Strategy) detailing the disruptive power of AI and offering guidance on how businesses should harness this potential going forward. They also issued a grave warning: adapt and utilise this technology or become obsolete in the very near future. WeAreBrain looks at this guide to AI strategy and reviews how it stands up in 2019, interrogating their forecast, and providing our two cents on what the next steps are to survive an AI world.

As many prominent business analysts and tech forecasters assert, we are currently undergoing the Fourth Wave of Industrial Revolution — the Digital Wave. This sees the heavy implementation of several emerging technologies which are causing vast disruptions to global businesses and the manner in which we think about business going forward into this new landscape. Leading the drive of advanced disruptive technologies is Artificial Intelligence (AI) with its machine learning and deep learning capabilities. These impressive technologies have resulted in game-changing advanced analytics and business algorithms which are beginning to alter the very fabric of traditional business outlooks.

Through their extensive research interviewing CEOs and CDOs of Gartner’s exclusive network, analysts Mike Rollings and Thomas Oestreich learnt three important pieces of information.

1. AI is now at the forefront of business transformation strategy

AI is only now beginning to show its true power as the technology readily improves. Early adopters of the technology with money to spend are already beginning to see the results of harnessing this tech within their business framework. It is therefore inevitable that AI’s involvement with businesses across the globe will increase and become more intimate, as the tech becomes more refined and economically viable. So business leaders will need to deal with this transition well. The aim will be to align people, processes and technology to a new business model, with AI leading the charge of analytics, forecasting and customer experience.

2. Advances in machine learning and deep learning will result in the technology becoming a part of almost anything purchased or implemented by a business

As this inevitable fact begins to gain traction among the business world, it will begin a torrent of need for qualified personnel. AI is only as good as the humans who are programming it, setting it tasks and analysing the outcome data. It is therefore crucial that businesses educate their staff in order for them to utilize the technology as it is meant to so that the business can harness the full potential of AI. Staff will be required to work together with AI and so an understanding of this disruptive technology within each business department is essential. As a business evolves into the digital era, so must its people.

3. Powerful AI agents of disruption become more readily adopted and demand an advanced outlook on AI’s role in business strategy

Rollings and Oestreich explain it perfectly. “Machine learning is a particularly powerful disruptive force that tends to be an ingredient in all forms of AI. Deep learning (often also called deep neural nets) takes that many steps farther by using algorithms that can identify patterns in data that humans would find hard to develop due to volume, complexity or other challenges. It is this ability to classify, identify patterns, and to develop insights into the data that helps the machine learning algorithm to learn from its own experiences with data, which makes machine learning a formidable tool for developing insights into data that was once challenging to analyse. This unique capability of AI could be used to improve the core value propositions with data insights, deeply understand customer segments, create opportunities to personalise customer relationships with detailed behavioral analysis, and open new channels that are part of go-to-market strategies”.

With this in mind, businesses will need to change their business strategy to accommodate for this new, disruptive and powerful technology. Business strategies have never had to work with AI before, so now it requires a complete reimagining of a business, its strategy and goals for the future. AI has provided more possibilities than ever before and soon companies will be reaching for the stars with their newfound capabilities, powered through AI.

4. Planning for the future

Rollings and Oestreich assert, “The advances in AI demand that data and analytics leaders examine their strategies and assess how AI can overcome previous hurdles and enable new game-changing capabilities. The advances also thrust organisations over an important threshold in how they approach data and analytics strategy development.

An increasing number of organizations are finding that AI doesn’t simply offer the potential to radically improve existing business activities, but instead creates the potential for data-driven business strategies like never before. This potential makes data and analytics a primary driver of strategy, which in turn mandates a more expansive examination of the potential for AI. It is no longer sufficient to simply look at AI in the manner in which we have typically assessed data and analytics strategy as a byproduct of other strategy work. As such, data and analytics leaders will not only need to understand the appropriate and emerging uses of AI but also become familiar with new strategy development practices in order to effectively assess the full potential of AI within the enterprise. This will allow leaders to maximize the potential for AI-infused solutions, enable new data-driven and data-enabled business models, and uncover opportunities for product and service innovation”.

At WeAreBrain we have a very similar outlook when it comes to the adoption and deployment of AI solutions. We have invested thousands of hours developing our own AI Enterprise automation solutions, which we have used to simplify many of our client’s processes while giving them the capacity to amplify their output. We also believe the data gathered and the subsequent rich analytics garnered from AI-driven strategy has the potential to change the way companies operate entirely.

5. Next steps

In order to realise the full potential of AI within an enterprise, Rollings and Oestreich insist that data and analytics leaders should do the following:

• Expand your strategy development repertoire by using frameworks such as the Business Model Canvas or the AI Canvas to develop a clear line of sight to business value and to assess AI’s relevance to the various business value components listed in Gartner’s data and analytics strategy compass

• Harness the disruptive potential of AI and machine learning in customer experiences by mapping the AI journey and applying outcome-driven innovation. Use these tools to meet nascent customer requirements that AI uniquely uncovers and do not forget to compare your top use cases with those applicable to your vertical markets.

• Address governance impacts by incorporating new regulatory and ethical considerations into your decision making; foster a data-driven culture and critical data science capabilities to address organizational impacts, and steer clear of the AI pitfalls associated with technology selection.

AI is a powerful and disruptive technology, one that is becoming increasingly more sophisticated. The benefits which AI offers businesses are exciting and will continue to evolve as the technology improves and becomes more intuitive. It is indeed the way of the future, and just like humans were sailing the seas before we flew in the skies, AI is business’s next big step in evolution.

Interested what opportunities AI will offer your organisation or would you like to learn more about Intelligent Enterprise Automation and Robotic Process Automation? Reach out and contact us for a demo of our Tur.ai platform.

Mario Grunitz

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