How AI is transforming the BPO industry and contact centers
Everyone is talking about AI, but which organizations are adopting it? BPOs are a great example, especially AI for internal CX strategies and contact centers.
Organizations wondering how to embrace AI should look no further than business process outsourcers.
Compared to other business sectors, BPOs have adopted AI at greater levels. This is likely because BPOs embrace digital transformation -- and, therefore, innovative technologies like AI -- for internal CX strategies, according to Robin Gareiss, CEO and principal analyst at Metrigy. While AI is not new to contact centers, BPOs that invest in newer technologies often have happier agents, leading to happier customers.
In the webinar, "AI & Automation: Setting the Stage for a BPO's CX Success," Gareiss and Tom Stanley, regional vice president of NICE Ltd., explored the pros, cons and use cases of AI in BPOs and their contact center agents.
"I know a lot of people get a little concerned about, 'Should I be using AI? Is it going to freak out my agents?' … But we're seeing it's a benefit. It improves longevity. It gives them answers they need," Gareiss said in the webinar.
How BPOs use AI
BPOs view AI investments as a higher priority than organizations in other industries, according to Metrigy research. Because of this, they are more likely to become trusted advisors for AI investments, as they have experience implementing AI strategies for themselves and their clients.
BPOs primarily use AI in the following ways:
- Agent assist. These technologies help contact center agents do their jobs more efficiently -- using screen pop-ups, sales suggestions and next best action recommendations -- which can create a more personalized CX. BPOs also have a lower average handle time than other industries due to better agent assist technologies.
- Conversational AI. While conversational AI can serve as a chatbot channel within contact centers, CX leaders can also use it internally to evaluate trends. For example, it could ask agents about their top drivers for success on a particular day, Gareiss said. It also offers more access to data across the organization, so agents can answer customers' questions more quickly.
- Sentiment analysis. This type of analysis can fall under agent assist technologies because it can help agents improve CX. Sentiment analysis uses natural language processing to gauge customers' emotions through their written words or tone of voice. So, if customers get frustrated, AI can transfer them to a live agent, or another agent better equipped to handle their issues.
- Text analytics. This analysis also falls under agent assist technologies, although it has less to do with customers' experiences. It's more suited to helping agents search through the organization's data quickly to answer specific questions. Additionally, it could identify key terms or phrases in a transcript to analyze a specific issue, how the agent solved it and what could have been done better.
- Self-service. Chatbots, FAQs and interactive voice response systems are the most common examples of AI self-service. These channels offer customers a route to independently solve their issues or answer their questions without talking to an agent. If contact center leaders maintain these channels and ensure they offer correct, up-to-date information, it can free up agents to help customers with more pressing issues.
- Bots. Nearly half of organizations employ chatbots, according to Metrigy. Whether a business uses chatbots, voice bots or any other type, over half of them have staff dedicated to ensure they function properly, so the bots end up creating jobs rather than taking them away from agents.
Many BPOs also report using generative AI in their workflows for tasks like meeting transcripts, content creation for self-service channels or summaries for customer feedback. These trials put BPOs ahead of other industries in GenAI use as well.
Pros and cons of AI in BPO industry
As BPOs are ahead of other industries in terms of AI adoption, they have experienced the highs and lows of the technology. The benefits include the following:
- Improves agents' experiences and efficiency.
- Boosts revenue and customer satisfaction.
- Enhances digital transformation strategies.
- Better supports existing agents by freeing up their time, giving them access to new and improved technologies and upskilling them.
- Gain a better understanding of AI technologies.
- Obtain and analyze more customer data.
However, challenges still abound with AI in BPOs. They include the following:
- Unfulfilled demand for properly skilled agents.
- Reduced need for outsourced contact centers.
- Potentially higher investments in AI and automation technologies.
- Becoming a trusted advisor in AI for clients.
- Integrations with clients' systems.
- Finding a system that meets an organization's specific needs.
Overall, BPOs offer other industries a look inside their potential futures with AI adoption -- especially after the outpouring of interest in GenAI when ChatGPT was launched in late 2022. Metrigy found AI adoption was lower than anticipated in 2023, with 36% of all organizations using AI in their contact centers, compared to 70% of BPOs. This experience puts BPOs in a position to aid other organizations -- including their own clients -- in their own AI adoption strategies.
"That gives them a lot of the experience internally -- like 'Hey, we've done this not only for ourselves, but for our clients.' And it really gives them that foundation [for digital transformation]," Gareiss said.
Michaela Goss is the senior site editor for TechTarget's customer experience and content management sites. She joined TechTarget as a writer and editor in 2018.
