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AI 360: Accelerating AI in the enterprise

The race to the tipping point is on

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The starting line

In some respects, artificial intelligence (AI) is old news. In the consumer market, conversational AI – think of Siri or Alexa – is commonplace in many homes.

In the enterprise, the story is a little different. As more people experience the benefits of AI in their personal lives, they expect the same in their business interactions too. But, while many business leaders understand the importance of AI and are keen to explore its possibilities, the consumer market is setting the standard, and enterprises risk disruption if they cannot keep up.

Businesses should be aware that an AI tipping point is looming. Progress that has been slow is set to become sudden and dramatic. "We predict that by 2025, companies that have adopted AI will be 10 times more efficient and have twice the market share of companies that have not," says Vikram Mahidhar, global business leader, AI solutions, at Genpact.

Some organizations are already making headway. AI-enabled businesses use technology to make informed decisions and predictions, spot risks and opportunities before their competitors, and anticipate customer needs to boost satisfaction, loyalty, and revenues. For businesses only just beginning to explore AI, developing and implementing their strategies at speed is essential. 

As we look at how different industries are using AI, it's clear there are still significant barriers to overcome. However, there is hope for a new approach that allows businesses to realize the benefits of AI faster than ever before.

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"Our prediction is that by 2025,companies that are AI leaders will have twice the market share of companies that have not adopted AI."

Five steps to accelerate AI

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Slow progress is no progress

Earlier this year, as part of our AI 360 series, we launched a survey of more than 500 senior executives and 4,000 consumers and workers.1 The research revealed that within large companies, a quarter of senior executives say they plan to fundamentally reimagine their businesses with AI by the end of 2021 (compared to 14% in 2017).

"Businesses are plowing ahead without a clear vision, and, when they hit obstacles, their AI program stalls."

Despite this ambition, the benefits of AI are not being realized as quickly as expected. In our research, respondents identified a number of barriers to AI adoption. The most challenging was a lack of clarity on where to use AI effectively.

This means businesses are plowing ahead without a clear vision, and, when they hit a roadblock, their AI program stalls. Even if they ­find ways to overcome the obstacles in the short term, it's unlikely their AI strategy will follow a connected approach that unites the business in the long term.

Disrupt or be disrupted

Banking is a prime example of the need for accelerated AI. Our AI 360 research shows that 97% of banks have implemented some form of AI. But, we're at a point where industries can no longer afford for AI to be on the fringes of an organization. It needs to be at its core – as the neural wiring, stitching the organization together. AI's potential to help banks grow revenue, manage risk, enhance customer experiences, drive innovation, and lower cost is too large to ignore.

It's not just banks that need to act. Every business is at risk of becoming an AI laggard as expectations for personalized, seamless user experiences carry over from the consumer to the business world. Enterprises must move from cumbersome legacy systems to more agile, digital technologies to meet their organizational goals and remain competitive.

As an example, AI gives consumer-goods companies an opportunity to get closer to their end customers. At present, retail giants control this relationship. Using AI, consumer goods firms can take back control by interpreting buying signals, spotting trends, and nimbly adapting products and promotions to customer needs. The longer they take to explore AI, the longer retail giants will hold the upper hand and the more time competitors will have to close the gap ­first.

To realize digital transformation, AI must be a fast-tracked priority for every enterprise. So, without time on your side, how can you accelerate your AI strategy without compromising on quality?

Fast-track AI. Go modular.

For many established enterprises, accelerating AI can feel impossible. With so many legacy, complex, and often disparate systems and processes in place, where do you begin? The answer: stop getting overwhelmed by the big picture and start thinking about modularity.

With a modular approach to technology, you can optimize interchangeable building blocks. As a result, your business can scale and refine processes at speed, rather than starting from scratch.

Sadly, this approach cannot be taken with AI. Until now. With prior training, pre-programmed AI solutions can plug and play into a company's core business processes – such as assessing a mortgage application or managing invoice exceptions – to improve experiences, accuracy, and efficiency at previously impossible speed. This eliminates the need for customized machine learning and iterations, shortening the path to digital transformation.

"Pre-programmed AI solutions can plug and play into a company's core business processes."

Context is king

Let's not forget, you must always consider technology in the context of your industry. Paul Roma is the former CEO and current chair of the life sciences advisory council at Ciox Health, the US healthcare market leader for clinical information exchange. Having led a major digital transformation strategy at the company, Roma says, "80% of the value of machine learning comes at the industry level, only 20% comes from the science itself. The heart of the matter is how to apply it to the industry, to the domain, and augment how humans are making decisions.

To Roma's point, an AI solution that monitors risk in the pharmaceutical industry is different from an AI solution that monitors risk in a lending portfolio. Both can use the same core AI platform but are trained with different datasets, semantics, and processes. Only when combined with the relevant context that people with deep industry and process knowledge bring, can AI applications deliver value.

"Forward-thinking organizations are already seeing the impact of pretrained AI solutions backed by industry expertise."

The path to victory

It's the combination of accelerated AI and industry expertise that will separate winners from losers. “Leaders will come down the AI path faster and solve the problems that laggards are trying to solve," says Genpact chief digital officer, Sanjay Srivastava. “If you can adopt an accelerated approach to AI with pretrained solutions, then you will see the benefits and keep yourself ahead of the marketplace, rather than being left behind."

Forward-thinking organizations are already seeing the impact of pretrained AI solutions backed by industry expertise. In the insurance industry, thanks to pretrained AI, a US company can now process hundreds of thousands of claims each week, which speeds up turnaround time to days from weeks, while improving decision accuracy. And, given the scale of fraud against the industry (estimated to be more than $30 billion every year in the US alone), AI can have a big impact on insurers' profitability and reduce customer churn from increased premiums. By analyzing data from a wide range of sources, including previous claims, customer information, and social media, AI can build predictive models to identify, score, and prioritize possible cases of fraud.

While AI adoption in the enterprise is currently a marathon, adoption in the consumer market is a sprint. Fortunately, using pretrained AI solutions, there's an opportunity to catch up. It's an accelerated approach to AI, relying on pretrained solutions backed by industry expertise, that will enable the most forward-thinking enterprises to move faster with AI and close the gap.

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