Unlocking the business opportunity of artificial intelligence

Today, if someone asked for thoughts on artificial intelligence (AI), your mind might paint a pop culture informed picture of a dystopian machine-ruled future or a chatbot with the lexicon of a seven year old.

That’s the problem with new technology. Our vision of the future is coloured by the realities of today, or in many cases, what we witnessed fifteen years ago in Minority Report.

Viewing AI through the lens of a futures market

It’s not a risky proposition to suppose that the worth of AI can rise within the future. IDC suggests that $41 billion are endowed in AI systems for enterprises by 2024, and Forrester comes thirteen.6 million new AI jobs are created within the next decade.

If you think that AI can play a much bigger role in business within the future, yesterday was a decent time to start the journey. Some businesses justify inaction by suggesting the technology is unproven; it introduces reputational and money risk to a business. Why not sit on your hands for 3 years, and sit up for the technology to mature.

Doing nothing may be a high risk strategy. to start with, initial movers profit massively from scaling their internal capabilities prior to their competitors, significantly during a white hot achievement market.

Second, to try and do nothing and to be seen doing nothing invitations aggressive competitors to actively target those corporations and their customers. Third, permitting competitors to form the market is to defer to a method you’ve got no management over.

Three areas of AI application

There square measure 3 immediate areas of business application for AI. the primary is development of virtual assistants, designed to act on behalf of humans so as to higher accomplish our goals.

Today, there’s a invasive trend for chatbots. this is often maybe unstartling given the world quality of instant electronic messaging (IM) platforms. The format is acquainted to anyone United Nations agency has used IM, and with IM platforms being a lot of standard than their social media equivalents, there’s an oversized school savvy audience.

WhatsApp alone has sends a lot of messages than SMS globally. shoppers just like the proven fact that electronic messaging works each as an instant, in addition as Associate in Nursing asynchronous, channel.

Today, chatbot adoption is fighting on 2 fronts. From a shopper perspective, if a chatbot isn’t a convenience upgrade on existing alternatives (such as Google search or mobile app functionality) the novelty price of chatbots can presently wear off. From a utility perspective, firms struggle to stay up with shopper expectations.

When Capital One launched one amongst the primary Alexa skills in March 2016, customers at once thought that they might conduct all their banking wants through it.

Capital One square measure early adopters of the platform and have learned a good deal within the last eighteen months, pushing Amazon and therefore the limits of the platform, in terms of metaphysics size and quality, on the approach.

AI application

Whilst chatbots might fade in time, the role of virtual assistants is here to remain. while these days several chatbots square measure simply the equivalent of a centre, interactive voice response (IVR) menu system or Associate in Nursing list information retrieval system, over time their ability to handle a lot of nuanced necessities and supply educated recommendation can grow.

Building sure-fire virtual assistants needs a mix of magic and logic. Magic to make compelling experiences that modification shopper behavior, and logic to make sensible algorithms that still learn and improve deciding.

A second space of immediate business profit is automation and augmentation. Automation of manual processes, notably in inheritance businesses with inheritance technology, has vital price base implications.

Whilst automaton method automation (RPA) is nothing new, the sensible application of machine learning to not simply convert a manual method into an automatic one, however {to do|to try to to|to try Associate in Nursingd do} therefore in an mortal approach, perpetually rising the effectiveness and potency of the method, may be a prime application for AI.

Augmenting workforces with AI driven applications is another supply productivity gain. several styles of client service interaction square measure currently a mix of human and machine response.

Machines will build individual service representatives a lot of productive by automating repetitive tasks and mechanically prompting responses to normally asked queries.

Inhibitors to value creation

Ultimately, the killer application of AI is the invention of new business models, products and services. It is alluring to think that a firm’s data contains a map to some hidden treasure of a previously undiscovered business model.

The reality is somewhat more mundane. Only those companies with access to the right analytical firepower, coupled with an ability to free their data from the shackles of legacy siloed databases, have a shot at legitimately creating new value from data. Both are serious undertakings with minimal shortcuts.

Talent availability is a serious inhibiter of artificial intelligence growth. Without a sustainable capability model, businesses are struggling to attract people with the relevant skills, particularly when trying to compete with Google, Amazon and Facebook. Given the low supply, high demand nature of the artificial intelligence labor market, workers are well compensated, with average salaries of $170k according to Paysa.

Legacy technology is the other hindrance to the implementation of artificial intelligence applications. Identifying previously unknown relationships within data requires the integration of disparate data sources. Silos are the enemy of integration.

Those companies that have migrated their data to the cloud, have built robust APIs and have reached a higher degree of digitisation are generally in a better place to generate value from their data.

The clock is ticking

There are two ways of looking at generating business value today from AI. One is to get tactical. Developing proof of concept prototypes, getting real consumer feedback, and developing the opportunity to upskill colleagues and learn by doing.

The process of creating a backlog of prioritised use cases along with their respective business cases can help to focus development in small achievable chunks, with each new application building on the underlying knowledge model.

The other is to take a longer term view, and begin to create the structure required to exist in a more AI mature world in three to five years’ time. While developing internal data analytics capabilities, migrating data from silos into an extensible cloud solution and building key strategic partnerships may not provide visceral evidence of progress in the short term, it is vital to long term sustainable success.

Either way, inaction is risky. As the world has been digitised, AI has begun to take off due to the exponential growth of data, reductions in costs of cloud computing and the scalability of virtual machines. Those that adopt an AI first mind-set early are in the best possible position to take advantage of this burgeoning field.

Manorama Singh

I re-write and share using words as a means to express ideas and emotions always allured me hence I now use my passion for writing as a means to earn a living. I have browsed and curated various articles for an array of categories on topics such as Technology and Updated.