Five ways to scale business strategy with AI

The enterprise world woke up to Artificial Intelligence (AI) in 2016. An AI software called Benjamin wrote the screenplay of a sci-fi movie. This movie “Sunspring” screened in the Sci-Fi-Film festival in London in summer 2016. The supercomputer Alpha Go beat Lee Sedol, the reigning world champion in Go. The potential of AI had arrived.

Ever since, Fortune 500 companies have started to grapple with what AI can mean to their business and their operations.

And as they experiment, a clear pattern is emerging. Anything which is a process can and will be taken over by AI & machine learning (ML). If one extrapolates this, then all normal processes and cases will be automated and the job of humans will be relegated to handling the complex exceptions.

As with any emerging technology, the only thing that is standing in the way of leveraging AI / ML is neither the technology nor its implementation. Instead, there are five factors that will inhibit or scale the growth of an organisation using AI/ML: The ability to imagine, the willingness to change, the rethinking of product design, mastering the art of partnering, and finally viewing AI as a paradigm for business change.

Critical Skill 1: Unleash the imagination of your workforce
The crux in AI & ML does not lie in the lack of technology, but rather the conjuring up of use cases. How do we enable each person in the organisation to think big and imagine what the future will be like, and picture him/herself in this picture. What is blocking this imagination? One of the culprits is the hierarchical organisation structures that inadvertently shape the mindsets of people and narrow their thinking. The creation and nurturing of communities within the organisation will enable talent and creativity to cross silos and organisational boundaries.

Critical Skill 2: Overcome the willingness to change
It is counterproductive to force intelligent technology down the throat of the entire enterprise. Instead, involve employees in designing the balance between investment in AI & ML, and maintaining the existing business.

Contrary to expectations, employees are far more willing to master new technology as they know that this will keep them employed.

This will unleash a new set of human talents that machines are currently unable to match — creativity, interpersonal communication and empathy. Leading to the creation of new jobs and responsibilities.

Critical Skill 3: Rethink existing product design & architecture patterns
Technologists have been designing deterministic systems since decades. Software products and systems are designed based on clarity of inputs and outputs. As we approach the AI world, systems learn how to deal with data through self-learning algorithms. And the art no longer lies in how to build systems with clear rules and logic. New skills will be required to build systems that constantly learn as more data is thrown at them. This will fundamentally reboot software development paradigms like requirement analysis, design and testing — whether done agile or waterfall.

Critical Skill 4: Master the art of scouting & partnering
Working with providers and technology platforms will undergo a significant change as we leave the realm of deterministic systems. Organisations will have to learn to rely on providers as part of the AI solutions are embedded in their offerings. The discussion will move away from “which partner delivers the best quality” . As AI is applied to each business process, companies will have to ask themselves whether AI in this case is a core competence or “whether a partner can be trusted to run AI ethically and competently within a business process”. Startups in the area of AI have sprung up like mushrooms — each having a narrow focus, lack of real investment capital and the access to the enterprise market. This is a huge matchmaking opportunity.

Partnering involves contracting for co-creation, joint success and sharing of the joint intellectual property created. Fortune 100 enterprises have fallen behind in the art of partnering at enterprise grade.

Critical Skill 5: View AI as a paradigm for business design
As the use cases of AI explode, organisations cannot afford to wait till first-movers in the industry show what is possible. The days of aiming to be the fast follower are over. Yet the pressure to act will depend a lot on how competitive the industry segment is. Even so, one can act ahead of the curve as industry segments merge. Manufacturing companies are tracking finance and retail companies in using AI in marketing. Insurance companies are adopting manufacturing paradigms like Digital Twins to predict the risk of the assets they insure. AI therefore should be seen not only as the means to improve the operations of an organisations, but rather fundamentally change the way that an organisation makes its revenue.

In conclusion: AI and ML have the power to redefine value chains globally. Market leaders should look at AI as a means of defending their pole positions, while others should use AI to reposition themselves during the disintegration of the value chain. The above five critical skills will be key in whether AI will play a role in the strategy execution of an organisation.

This will not be an easy ask — it will require the extrapolation from data and algorithms to concrete product ideas and a forced investment even when the returns and goal horizons are not yet clear.

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