Getting Real Results Today with Artificial Intelligence

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Once the stuff of science fiction stories, artificial intelligence (AI) is moving into the mainstream. Practical applications are rapidly emerging and businesses are exploiting AI apps to deliver significant value.

In particular, cognitive computing capabilities are now performing many routine, mundane tasks that humans have been saddled with in the past. The real payoff is that cognitive apps are handling those tasks faster and at a lower cost. Examples include customer service bots that walk users through installing software and smart, context-based recommendations that give novice agents the ability to perform like experts.

There still are many tasks that machines won’t be able to perform, at least not in the foreseeable future. The ability of humans to exhibit leadership, express empathy, and teach new skills would be exceedingly difficult to transfer to machines. In a broad sense, anything that requires judgment is better left to humans while anything that can be predicted can be handled by a machine. For example, machines can quickly analyze huge volumes of historical and real-time weather data to make accurate forecasts.

AI will go through multiple phases as it matures. Today, successful AI applications are narrowly focused on areas in which cognitive AI, including machine learning and natural language processing, can facilitate, automate, or accelerate tasks in specific domains such as information technology, human resources, agriculture, and healthcare.

We’re also seeing progress in more generalized areas such as self-driving cars and voice assistants. Major corporations are focusing significant resources on making these technologies enterprise grade with respect to security, governance, and other important characteristics.

Empowering IT with AI

In today’s enterprise, the IT domain is well-suited for automation, which makes it a prime candidate for cognitive AI. That’s because IT has been standardizing processes for decades—think IT Infrastructure Library (ITIL)—and the more a process is refined and standardized, the better its fit for automation.

That’s fortuitous because IT has become integral to virtually every business process and has become a key driver of innovation in virtually every industry. AI provides a powerful engine for automation, empowering IT to rapidly scale to meet the growing demand for digital services and reinforcing IT’s role as a key player in directly influencing business outcomes.

The question IT professionals are struggling with is how to best take advantage of AI technologies such as machine learning and natural language processing. The answer is counterintuitive. They have to start by forgetting about technology. Instead they need to focus on the business outcomes they want to achieve, for example:

  • Improving the uptime of business-critical systems by speeding the detection and resolution of issues that might disrupt those systems
  • Reducing infrastructure costs by accurately aligning available capacity with consumption needs.

Streamlining IT service management

One key area for AI is IT service management (ITSM). Here, the desired business outcome is to deliver higher-quality services to more people faster and more reliably. Speed and agility increase a company’s efficiency as well as its competitiveness. Cognitive AI helps IT achieve this outcome by increasing the level of automation in all phases of the service lifecycle, including provisioning a service, maintaining its health, and supporting the people who use it.

In the service management arena, the system of record is an ITSM solution such as Remedy Service Management Suite. The lifeblood of the IT organization lives in the workflows and knowledge base that reside in this system of record. When coupled with an ITSM solution, AI technologies bring intelligence to the workflows, enabling the system to make decisions that previously required human intervention.

Adding intelligence to workflows enables the automation of many of the routine tasks that have been traditionally handled by service desk agents. The AI-enabled ITSM solution analyzes the work that live agents do to address these tasks, learning the steps taken and the decisions made. The solution then leverages what it learns to increase the level of automation and act as a virtual assistant to augment the live agent.

AI-driven automation makes for a more powerful solution that benefits everyone. A virtual agent integrated with service request management simplifies the request process by allowing employees to use natural language in making requests. Intelligent recommendations for problem resolution empower support teams to fix problems faster. Infrastructure owners can leverage machine learning to assess risk before approving changes.

AI-enabled ITSM makes human agents smarter in two key ways:

  • Auto mapping determines the values for certain fields on a form and populates those fields automatically. For a change request, auto mapping might determine the appropriate assignment group, establish the business priority, and assess the potential risk posed by the requested change.
  • Fulfiller assistance determines how to fix an incident or fulfill a request and guides the agents tasked with resolution or fulfillment. For example, in response to a request for a virtual machine, the AI assistant recommends where in the cloud the machine should be provisioned, how it should be configured, and how much storage it will need.

Again, the key here is to think in terms of the desired outcomes and the KPIs that measure them. For a service desk, the desired outcomes might be higher agent productivity, faster response, and lower support costs. Here, the relevant KPIs would include mean time to repair (MTTR) and first-call resolution rates.

Reaping the benefits

The most pragmatic way to derive value from AI today is to take a focused, incremental approach and identify enterprise services most likely to benefit from automation. That means determining specific business outcomes you need to achieve and applying AI to achieve those outcomes. By enlisting AI as a partner in service management, IT organizations can help achieve corporate goals and objectives. For example:

  • By speeding response to customer requests, the service desk staff can increase customer satisfaction, strengthening customer loyalty and driving higher revenues.
  • By boosting service desk agent productivity, the staff can lower IT costs, thereby boosting profitability.

Savvy IT organizations are already reaping the benefits of cognitive AI, and, considering the nascent nature of the AI/service management partnership, the future is certainly exciting.

For more information on cognitive service management, click here.

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Introducing Cognitive Service Management

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These postings are my own and do not necessarily represent BMC's position, strategies, or opinion.

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Dan Turchin

Dan Turchin

Dan Turchin is the co-founder and chief product officer of Astound, the leading provider of machine learning and natural language processing solutions for enterprise service management.

Prior to Astound, Dan was vice president of product at DevOps leader BigPanda, chief product officer at security analytics company AccelOps (now Fortinet), and a senior director of product strategy at ServiceNow.

In 2000, Dan co-founded mobile enterprise machine learning company Aeroprise and served as CEO until it was acquired in 2010 by BMC Software. He was also a founding board member at Rhomobile prior to its acquisition by Motorola.

Dan is passionate about building great teams that build great products that solve hard problems that change lives. He's a big fan of Orwell, Dr. Seuss, youth soccer, adventure sports, and Tynker. Dan has BS and BA degrees from Stanford University.