ai: Five ways to succeed in the digital world

By Sanjay Srivastava

As organizations progress along their digital transformation journeys in earnest, here are five trends they should keep top-of-mind to drive competitive abilities.

“Transformation-as-a-service” accelerates time-to-value. The largest enterprises are embedding AI and machine learning tools throughout their organizations to help analyze data, increase efficiencies, predict consumer behaviors, gain competitive insights, and fundamentally transform their major operations and services.

Others are finding that the time and resources it takes to get up and running make it difficult to transform their operations at scale, and drive meaningful, enterprise-wide outcomes at speed. Transformation-as-a-service lets these organizations gain access to AI, data, cloud, mobility, and other digital technologies with basic tasks and knowledge already “baked in.” The model helps them realize benefits faster, more quickly shift their technology mix in response to evolving customer and competitive needs.

Customer experience is the new battleground. Business leaders recognize that soon there will be two types of companies: those that effectively reimagine the customer experience (CX) and those whose sub-par CX capabilities will ultimately drive them out of business. CX success in the digital age isn’t about responding to customer demands; it’s about predicting them and offering products and services that address those predictions.

To excel in CX, organizations need to unlock insights from alternative data sources, generate real-time competitive insights, and build rapid-response decision-making into differentiated, personalized experience programs. Doing so will help them improve their top line, reduce errors and costs, and realize sticky, return customers.

“Humans-in-the-loop” are becoming more valuable. A 2019 article stated that by 2025, 463 exabytes of data, the equivalent of 212,765,957 DVDs, will likely be created every day. This data explosion is being fueled by AI and improvements in analytics. Today, enterprise applications can’t deliver more than 80 percent accuracy. Humans must take care of the other 20 percent to train the AI models and address the last mile of decision-making.

Given this shift, and the resulting evolution of job functions and requirements, there is a vital need to reskill the “humans-in-the-loop.” However, there’s a large disconnect in how reskilling efforts are perceived. Our research shows that only 35 percent of workers said their companies have reskilling options, while 53 percent of senior executives said they do. One of the best ways to close this gap is to replace classroom-based training with virtual programs that harness the collective intelligence of experts throughout the organization.

Ethical governance of data, AI, and digital. Consumers and governments alike are becoming increasingly concerned about how data is being used by AI-driven technologies. The concerns are so great – with issues ranging from algorithms that drive credit limits to the use of facial recognition software for myriad reasons – that governmental bodies around the world are taking action.

To help eliminate stakeholders’ and consumers’ worries about unethical or biased data use, we expect that many organizations will add Digital Ethics Officers to their leadership team.

These officers will have multiple responsibilities: implementing ethical frameworks to make appropriate decisions about new technologies; addressing considerations like data security and bias; looking ahead to future technology challenges; building new standards of technology governance; and establishing new check-and-balance systems to ensure preventative measures remain effective.

AI accelerators can democratize technology. We predict that by 2025, AI leaders will be ten times more efficient than and hold twice the market share of organizations that fail to embrace the technology. Indeed, most executives recognize that breaking down time and resource barriers to accelerate AI adoption is becoming a matter of survival for their businesses.

Pre-trained AI accelerators can help organizations democratize technology through the enterprise. These building blocks are already trained with the necessary domain expertise, so it can quickly provide people with the tools they need to make better decisions.

The author is chief digital officer of Genpact. Views expressed are personal.)

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