Leverage Generative AI in Business Operations to Thrive in a Tight Economy

The relevance and impact of AI and automation in high inflation conditions become even more crucial. Faced with the pressures of inflation, businesses are looking for innovative ways to optimize operations, maximize efficiency, save time, reduce costs, and maintain productivity. AI and automation technologies, like ChatGPT & Generative AI-powered chatbots from Aisera, are at the forefront of these efforts, offering potential solutions that can help businesses & enable companies to navigate through these challenging times.

Aisera’s CMO, Murali Nemani, sets out challenges that business leaders face in order to thrive and stay competitive, in a tight economy amidst fierce macro pressures.

Moderator Will McKeon-White is a Service Desk Analyst at Forrester, an expert in the field of Service Desk and Conversational AI. Panelist Brian McGuinness is VP of IT Operations at Chegg, a leading education technology provider of key student services. Daniel Heras represents epic fashion innovator Gap as a Product Executive. The panel is completed by Muddu Sudhakar, noted serial entrepreneur and CEO of Aisera.

Aisera’s domain-specific large language models (LLMs) use deep learning techniques for natural language processing and massive data sets to engage employers and potential customers. Aisera’s Conversational AI Platform not only understands processes but generates highly personalized, contextually relevant responses; it offers empathy in resolving questions from users and customers, taking action, and generating workflows. Aisera built over a trillion intent phrases customized to these environments so as to deeply understand the needs people are speaking of and asking about.

Aisera delivers access and integration to your knowledge bases, ticketing systems, knowledge environment, tools and infrastructure. Our Generative AI solution interface through a collaboration platform like MS Teams or Slack—or as a voice solution enlisting call centers through classic mobile apps or desktop chatbots.

Transparency in Generative AI technology is crucial in building trust and mitigating concerns about potential risks in the use of Generative AI tools, such as those implemented in the IT department. It’s vital for users and business leaders to have confidence that these Generative AI tools are built with integrity, deliver accurate and dependable outcomes, and adhere to established ethical principles.

AI transparency involves ensuring the system’s processes and decisions are understandable, observable, explainable, and accountable. Although a Generative AI tool can provide a response, the path it took to that response can often remain a mystery.

Which parameters did it consider? Does it uphold the same principles that we, as humans, abide by? Without transparency in Generative AI technology, addressing these questions and comprehending machine thought processes can be a significant challenge.

Certain LLMs embed “hallucinations”— random inaccuracies and even falsehoods within their generated content. We confine our Generative AI within guardrails so that it cannot “experiment” and plague users with nonsensical content or health and safety risks.

Yet another concern is reinforcement and collective learning so a system in place doesn’t have to keep manually updating and training but rather relies on continuous learning. Before generating code to answer the user’s query, the Generative AI will analyze vast amounts of existing data sets and also identify patterns on which content format is preferred by the user to serve personalized high-quality content and resolution.

Workflows and integrations too are vital features and provide a significant advantage — the capability of the system to solve their problem and automatically take action on the user’s behalf. Finally, the deployment model is essential in helping customers function in a scalable and hybrid environment.

Quite simply, humans doing this work are overwhelmed, says Will. The “small but mighty” model, despite some wildly impressive results, just can’t keep up:

64% of employees say they avoid the service desk

65% of employees declare they have issues the service desk cannot fix

These stats are the best reason to start with IT as the primary use case to drive immediate value and ROI. You can both improve employee experience PLUS reduce cost. Also, we strongly recommend you make sure that knowledge articles, workflows, and policies are accurate and up to date.

Chegg’s initial assessment revealed a lot of really enthusiastic support people, but the processes were immature: “63% of our tickets were for access requests and distribution lists!” Chegg needed to scale quickly and avoid burdening IT techs with problems that should be handled by bots. Aisera and Chegg programmed a “sassy” likable AI bot named “Shelly” to deliver ‘right now’ solutions.

Gap’s internal-facing bot, nicknamed “Stitch,” addresses issues 24/7 for a global workforce of 150,000 and speeds answers in MS Teams, Slack, or on Gap’s intranet site.

After choosing Aisera, Gap went live within six weeks. Over the last 1.5 years, they’ve expanded beyond IT to HR, store support—and more with Generative AI. Daniel notes that a key challenge for businesses is getting buy-in, but positive metrics speak for themselves.

For example, they had the challenge of migrating 16,000 corporate employees to a new mobile device management platform. After anticipating six months and tickets in the thousands, the task was done within weeks—and generated only 500 tickets total! “We know for sure that we saved the company millions.”

What Gap loves about Aisera is that we have the ‘keys to the car’ to resolve customer complaints and system issues without waiting.

One of Chegg’s major customer feedback gripes had been that people had to wait ‘forever’. Immediately after launching, Chegg leaped to 80% auto resolution—and 98% satisfaction this quarter! Thanks to Aisera and the Shelly bot, the IT team can maintain an under-five-minute SLA and many first-touch resolutions.

For Chegg, it was super-critical to have a knowledge manager on the team when they launched to ensure that internal KBs were fine-tuned and ready to go.

For Brian at Chegg, “the sweet spot of using Generative AI along with your own curated knowledge is in leveraging it for content creation. My view for content creation is getting the conversations set up properly and trained against curated content for the best user experience.”

Will: Muddu, how are you thinking about yourself in the broader AI systems? What is your vision for the future here?

Muddu: Many of the use cases are going to evolve as we continue with our enterprise AI Copilot deployments in the enterprise. The key is not allowing Generative AI to ‘hallucinate’ and enterprises want to protect their intellectual property and ensure they have an AI solution that’s transparent in its foundation models.

#1 In addition to self-service, there’s a tremendous opportunity for customer support, care, and service elements—empowering them and CSAT scores.

#2 Aisera offers an AI assessment with the ability to go in and closely examine your knowledge bases, tickets, and support logs.

#3 We can serve people with a POC and a demo, so they can start seeing what this technology means for business and their organization.

To learn how to bring the power of ChatGPT and Generative AI to your company, watch the on-demand webinar or reach out to us for a custom demo.