AI is enabling firms to move to outcome-based approaches, and SLAs need to evolve accordingly.

There was a time when businesses deployed artificial intelligence (AI) to automate existing, rules-based processes.

That was then. Today, some leading companies are going steps further, using advanced AI to implement outcome-based approaches.

As companies make the transition, a critical consideration for business leaders: re-thinking how they structure their service-level agreements (SLAs).

Why? For one thing, when a client defines business outcomes, service providers should be empowered to determine how best to achieve those outcomes.

Help desks, for example. In the past, help desk SLAs were typically structured with the stipulation that a certain percentage of customer inquiries or complaints were to be resolved in a specific amount of time, and the process might be based on rigid rules, like first-in, first-out (FIFO), to help prioritize responses.

Nowadays, sophisticated natural-language processing algorithms can be used to help identify issues faster and enable better prioritization based on a variety of criteria, including the urgency of a customer’s need. Moreover, such AI systems might be adept at handling perhaps 80 percent of emails with routine requests, leaving the remaining 20 percent to be handled by humans, who can then focus on the more complex cases, including those involving dissatisfied customers.

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By: Suraj G Jadhav, Accenture Operations

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