For the moment, forget all the high profiled media stories about the danger of artificial intelligence (AI). These arguments are based on what AI might become, not on what it is doing now. Business leaders like Steve Wozniak have joined iconic scientists like Stephen Hawking in warning that even benevolent AI could rapidly become dangerous simply though inadequate concern for human safety.

Those discussions have value, but this is not the place for them. What matters in this discussion is the nuts and bolts of how AI — as it exists in the real world today — can impact revenues and drive innovation within Steven Covey’s Three Horizons.

Horizon Refresher

As a refresher, McKinsey defines Horizon One (H1) as incremental enhancements to core businesses that are already well-associated with the brand. The key concept here is “Maximize.” Horizon Two (H2) opens a window into the exciting world of practical magic where entrepreneurs convert resources into wealth. These are the solid business ventures that could take off with the right investment. The key concept here is “Develop.” Horizon Three (H3) is the hazy realm of visionaries who redefine the possible with thought experiments, research projects, pilot programs and theoretical business models. The key concept here is “Imagine.”

For a more detailed review of how to act strategically on all three Horizons at the same time, consult Magnus Penkers related blog published for Drucker Forum “Organizing for Simultaneous Innovation Capability.” The point is that for all three Horizons, AI can and should hold an elemental significance for innovative businesses. Many have already begun to profit from strategic deployments of these non-local, silicon-based brains. Here’s how.

H1 Innovation: Radical Improvement

Some of the most successful advances in AI can be observed in the automatic translation of natural languages. For example, the Wall Street Journal announced this year that “The Language Barrier Is About to Fall” thanks to real-time AI translation inside earpieces. Similar advances have brought AI applications for automatic first-line support, advanced data search and price optimisation.

Collaborative development experiments with open source AI from Google, Facebook and Microsoft are making mobile apps and the Internet of Things faster and smarter in surprising ways. That’s partly why Gartner predicted that AI-driven technologies would certainly be the next disruptor for the world of enterprise software in the very near future.

H2 Innovation: Business Model Redefinition

These AI applications are, by definition, still in formative stages, but the outline of what is to come is gaining clarity. The Economic Forum at Davos this year referred to these proposals collectively as The Fourth Industrial Revolution.

Many B2B verticals are expanding to become B2B2C due to more intelligent digitalisation, customisation and smart interactions between customers and their clients. This is also known as forward integration in the supply chain, to distinguish these developments from backward integrations.

Backward integration using AI refers to businesses that encourage customers to take a larger role in the initial design process. End customers can help construct and build items they are just for them. This sort of self-service production line relies on company materials and services, like additive manufacturing (also called 3D printing) of individual items.

Some companies like Inbenta are experimenting with a range of service offerings up and down the supply chain. At the center of their value proposition is an AI program that understands natural language queries.

Cutting out the middleman opens up many new business models that could disrupt a host of industries. Basically, any vertical with a supply chain is a potential target for industry redefinition using AI. Some, like Alibaba’s eCommerce platform, are going for volume (using AI from a sales and logistic perspective). Others go for closer customer intimacy but using AI to make it all cost-efficient and scalable.

H3 Innovation: Intersection of Possibilities

In the speculative future, unrelated disciplines mesh to create original realities that no one can successfully predict. When Dr. Vannevar Bush wrote “As We May Think” in 1945, he predicted the web with eerie accuracy, but not the vast reinvention of society that arose from this global neural network. The logarithmic technological surges over the past few decades have outpaced forecasts and even credulity.

What companies need to do to push themselves on H3 projects in AI is to create an open innovation place for stakeholders where impossibilities are irrelevant. Companies can support university-led research or partner with deep learning organizations like Baidu’s Silicon Valley AI Lab. These are controlled environments where visionaries can explore ideas related to singularity studies, such as picotechnology for matter compilers, bio-AI convergence, transhuman wellness, commercial applications for exotic materials and the future of mankind in space exploration.

The Natural Progression

The simple truth is that AI should not be considered as something apart from humanity. It is as much a part of the human experience as language or commerce. AI arose as a natural progression from the first mathematicians and it will be there to help take global culture to its next plateau. [bctt tweet=”The simple truth is that AI should not be considered as something apart from humanity. It is as much a part of the human experience as language or commerce. AI arose as a natural progression from the first mathematicians and it will be there to help take global culture to its next plateau.” username=”@InnoSurvey”]In the meantime, there are many profitable and easily implemented solutions on the market right now to deploy for greater productivity and profitability. From decision-making to security to customisation, AI deserves to have a seat at the strategic table driving for innovations at all three horizons.