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Is AI Really the Answer?

Is AI really the answer

When considering where AI can make an immediate impact on IT operations, one application stands head and shoulders above others: hyperscale automation with intelligence.

Artificial intelligence (AI) has been hailed as the answer to just about every IT problem, including eliminating the dreaded skills gap, supercharging productivity, securing networks and ensuring competitiveness. Its potential seems unlimited, and no one wants to get left behind.  

However, despite the ongoing – and mostly justified – hype cycle around AI, it’s imperative that business leaders cut through the noise to understand how AI can be applied to their business, and which applications of AI offer the most promise right now – not next year or in the coming decade.

When considering where AI can make a major impact on IT operations, one application stands head and shoulders above others in terms providing the capability to drive dramatic returns in efficiency and productivity right now: hyperscale automation with intelligence.

How AI works

First, let’s break down exactly what hyperscale automation is, how it works and the impact it can have on an organization. Hyperscale automation is achieved through the combination of process automation software and AI to add cognitive capabilities within business processes, and a third technique called “process mining” which is all about the discovery and surfacing of business processes that may be unknown. When implemented, it provides total discovery, mapping and measuring of business processes followed by automation on a scale that wasn’t even possible just a short time ago.

The practical impact of this technology is that it allows businesses to maximize the efficiency and capacity of their operations, enabling them to offer differentiated capabilities in the market that wouldn’t be possible without hyperscale automation. When applied correctly, it can have an exponential impact on business outcomes by augmenting human capability with hyper-automation and AI to fundamentally change the capacity that each employee can reach. 

A prime example of how hyperscale automation effectively augments human capability is in how quickly it can make mistakes and course correct as a result. For example, a human can make a mistake while completing a certain manual business process once or twice an hour, adding latency to a workflow and resulting in an unwanted outcome. Hyperscale automation, by comparison, can make those same process mistakes in seconds, make corrections more quickly, and re-evaluate the mistaken decision in context so it does not repeat the mistake.

The result is that mistakes, corrections and learning happen in a matter of seconds with automation, freeing up human talent to focus on more sophisticated tasks.

AI In the marketplace

Going further, hyperscale automation can not only improve efficiency but also provide predictive capabilities that can be transformative. A great example is the solution one of our partners, Intelygenz, implemented with a renewable energy company.

In the U.S., the sell back energy market is most profitable when companies can be highly accurate in estimating how much energy they’re going to put on the transmission lines. For traditional energy producers this task can be straightforward – coal producers need to estimate how many shovels of coal they need to put on the fire and nuclear power producers need to know how many rods of uranium they’ll need to put in the reactor. Knowing exactly how much energy they can put on transmission lines allows them to operate at the highest level possible.

For renewable energy – especially wind turbines – it’s very hard to predict how much energy to put on the transmission lines because of dynamic conditions in which the energy is created. As a result, companies end up being very conservative with output, because if there are inconsistences between how much energy they put on transmission lines and how much energy they say they’re going to put on transmission lines, the consequences can be severe, including loss of licensing to operate.

Intelygenz’s renewable energy customer asked them if their technology could predict the amount of power that will come out of their network in advance. Using hyperscale automation, they were able to take all the data, including meteorology data, that comes off every wind turbine and from partners in the field, to give them the capability of accurately predicting their power output in advance, resulting in greater confidence for committing to power delivery schedules and delivering.

Challenges to AI Deployment

As demonstrated, hyperscale automation is a powerful application of AI that can be used right now to transform businesses processes, realize new capabilities and develop a competitive edge. However, the major challenge organizations need overcome to deploy it is not a technological challenge, rather it’s a human challenge.

We’ve seen time and again the biggest barrier to adoption of hyperscale automation is cultural resistance within organizations with some employees seeing this powerful AI as a threat to their livelihoods. Far from being a job replacer, hyperscale automation is a talent augmenter. It’s not meant to replace humans, rather it’s most effectively deployed in partnership with human intelligence, and organizations that internalize this dynamic are the primary beneficiaries of the technology.

Real AI Results, Right Now

While AI is sure to make enormous advances in the coming years, it’s already having transformative effects on businesses and organizations across industries in terms of automating processes and augmenting human talent. For businesses wishing to digitally transform, the promise of AI is no longer something that’s year’s away – it’s here now and it’s driving real results.

This article was originally featured in CIO.

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