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This is already an AI-driven world regardless of Elon Musk’s fears, isn’t it? And the goal of each business today is to learn how to live with it and how to take advantage of the AI tech to achieve a successful digital transformation. Why is it critical?

IDC predicts AI corporate market will reach $57.6 billion in 2021, significantly more than the $12 billion spent last year. PwC estimates that in 2030 AI would contribute up to $15.7 trillion to the global economy. This figure is higher than the current output of China and India combined. Furthermore, a recent Accenture report says AI will contribute £654 billion to the UK economy alone by 2035. And according to Accenture’s MD Vinod Patel, “a significant portion of that will be outsourced to third-party service providers. Increasingly, organizations are looking at external parties to drive innovation.”

In this article, I’m going to explore in what particular ways AI outsourcing will impact organizations’ digital transformation journey as well as Robotic Process Automation (RPA) in the months to come.

RPA Demystified

In an AI-driven environment, robotic process automation (RPA) is a major force behind the digital transformation. Tech giants like AT&T, IBM, Deloitte, and Dell are already adopting RPA at a head-spinning rate. Yesteryear, 16 case studies conducted by the London School of Economics demonstrated clearly that return on investment from using RPA could range between 30% and a staggering 200%. The 2017 ISG Automation Index Report states that 72% of companies will have adopted RPA by 2019. Moreover, as the research indicates further, IT operations will be the main area of its impact.

As an integral part of a larger AI concept, RPA is, in essence, the complete automation of routine, repetitive, and rule-based tasks such as:

  • Data capturing, validating and processing;
  • Predictive analytics based on recorded data and behavioral patterns;
  • User and customer communication based on pre-established protocols, etc.

In fact, RPA is capable of providing high-volume IT support and streamline financial and customer services as well as HR processes. Understandably, financial and manufacturing companies are pioneering its adoption, although other industries are catching up, tool. But, there’s one huge but to it! The total cost of implementation!

Introducing RPA is a very costly and resource-intensive endeavor. The cost is so high that even tech giants rely on third-party service providers. The reasons why enterprises choose not to develop their AI assets in-house are numerous, but they all boil down to the lack of resources such as timemoney and expertise.

Today, like any other industry, IT outsourcing (ITO) is undergoing a major transformation with key focuses being shifted from pure software development/IT cost reduction and increased time to market to accessing hard-to-find tech expertise, gaining niche-specific and tribal knowledge, and sourcing innovative skills and approaches for building and developing in-house competencies.

Is AI Outsourcing a Rescue Ranger?

Having turned from sci-fi to reality, AI is sure to transform every existing industry and vertical.

The smartest and the fastest ITO providers are already busy developing RPA offerings for their clients. And they are not just doing that to gain a competitive edge and stay ahead of the curve. They’re acting proactively and they tend to be ready when AI goes mainstream. They have to meet the rapidly growing market demand for industry-specific AI solutions, and the sooner they do it, the faster they’ll yield commercial results.

No secret that many enterprises today are facing infrastructure limitations: some of their critical operations run on legacy applications and hardware. For them, developing AI solutions in-house and deploying them on existing capacities would mean jeopardizing business continuity and disrupting workflow. On the other hand, replacing outsourced AI solutions, if they don’t meet expectations, is easier and better justified from a security standpoint.

With data analytics and machine learning experts demanding salaries and compensation packages that defy imagination, hiring a qualified professional could take months, if not years. Moreover, finding an employee with an industry-specific set of skills can be even harder. The demand for these specialists exceeds supply, while artificial intelligence outsourcing companies have access to talent pools worldwide.

For non-IT companies, educating their own employees to the level where they could develop complex AI tools would require investing time and money into something with a highly unpredictable outcome. An outsourcing model, with a dedicated development team working exclusively on crafting an AI solution tailored specifically to the organization’s unique needs, looks much more attractive.

For businesses, it’s ultimately more beneficial to focus on critical evaluation of their core processes — which of them could be painlessly automated, and, conversely, which cannot run without human supervision. Having this understanding is crucial before forging a partnership with an AI outsourcing provider.

The story of Vestas Wind Systems collaboration with a machine learning provider SirionLabs is a spectacular example of such a partnership. What started out as a tactical decision during an economic recession in 2015 brought 300% ROI to the Danish manufacturer of wind turbines during the first year of collaboration alone.

The company had SirionLabs leverage machine learning to manage contractual issues. “They can bring us those new technologies much faster and better than we could develop it ourselves,”— Vestas IT Leader Henrik Stefansen told Diginomica.

In fact, Stefansen estimated, developing such algorithms in-house would have required hiring 4 IT specialists.

That’s probably one element that surprised me a little bit — how much energy I had to put into my own organization to get my own colleagues to work in these new processes,” — he said.

Commenting on the current state of AI outsourcing in Europe, Vladimir Potapenko, CEO and Co-Founder of an international outsourcing company 8allocate says:

“We see a growing demand for AI solutions outsourcing from many Western European companies. Driven by the lack and/or a very high cost of onshore AI developers and experts in machine learning, NLP and other AI-based technologies, many view outsourcing as their last resort.”

One of the UK’s leading content and media service providers has successfully launched a mobile platform similar to 9gag and Reddit. Their goal was to enhance platform monetization by increasing user loyalty, engagement, and responsiveness to CTAs. Using AI algorithms for data analytics was the most viable solution, so the company came to 8allocate with their NLP, text mining and deep learning outsourcing request.

As Vladimir told me, using offshore AI capacities, the client was able to increase revenue by 25% within just one year after deployment.

But what’s even more important is the fact the company got a full-fledged AI and data science department offshore. From now on, they can always rely on their remote team to be the main “conductor” of long-term digital transformation,” concludes Vladimir.

The Next Generation of ITO

Yet, the main reason why AI outsourcing is likely to thrive is AI’s double-edged potential: although it has great transformative power, it can bring business to ruin if implemented incorrectly. Enterprises have to pass through a tight bottleneck: not using RPA will push them out of competition, while failing to use it properly could seriously disrupt their business operations. AI outsourcing remains a reasonable alternative under these circumstances.

A recent IDC research claims that the constantly growing AI solutions market will exceed $52 billion in 2021. To have a good bite of the pie, ITO companies have to undergo a radical makeover by honing their AI skills and restructuring the services they provide. Today, enterprises in long-established partnerships with outsourcing companies increasingly demand that they provide RPA and reskill their experts to embrace innovations. If they don’t comply, clients are ready to opt for onshore plus RPA solutions, instead of sticking with a purely offshore model. They are also considering using robots over humans.

Conclusion

In fact, the entire ITO business model will have to be reinvented. As far as AI outsourcing is concerned, territorial price arbitrage will no longer be the main source of revenue — ultimately, it’s the technological expertise and the quality of services that will keep them on top of the game.

Source: B2C

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