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Generative AI for customer experience. Should you outsource or stay in-house?

“I've been looking at salaries … for anybody that knows anything about generative AI and they're not just six figures. They're double six figures or triple six figures … It's going to be very hard to train and retain staff."

This quote, from Julie Mohr, principal analyst at Forrester Research, appeared in a TechTarget article about how generative AI can improve knowledge management. The article went on to say:

“Organizations that choose to build their own LLMs [large language models] must heavily invest in employee training and prepare for high attrition rates. For most organizations, existing vendors offer the simplest generative AI implementation method.”

Working at a company that fine tunes LLMs and implements generative AI to optimize customer experience (CX), these quotes resonated with me. However, it’s not just the human capital cost that tips the scales in favor of outsourcing generative AI implementation.

If you’re thinking about outsourcing generative AI to a third party, here are three areas to consider:

#1 Generative AI consideration: customer experience

According to Forbes, nearly 75% of consumers say they’re likely to buy from a brand based entirely on their experience with that brand – regardless of price or product.

No matter what industry you’re in, customer experience can – and should – be your competitive advantage. So, when it comes to applying generative AI to any aspect of the customer experience, you need to get it right.

With AI you can do a lot to improve customer experience. You can deploy intelligent virtual agents (IVA) that make self-service easier, and stand up advanced knowledge management, which can reduce friction by continuously updating knowledge articles and speeding up problem resolution. But before you implement any of these tools, it helps to have a strong, and well-documented customer experience foundation. Customer journey maps, voice of the customer (VOC) programs, and CX process mapping are foundational elements that help inform the smart deployment of AI within the customer journey.

Applying automation technology, like AI, to any point in the customer experience introduces both risk and reward to the equation. If you get it wrong, you risk alienating your customers and inadvertently making it harder to interact with your brand. That’s why you need to ensure that you have a strong CX foundation in place and know precisely how and where to improve it with AI.

#2 Generative AI consideration: data expertise

Tools like ChatGPT have made generative AI seem so simple that business leaders may be tempted to believe they don’t need a data scientist to implement generative AI within their operations. We need to dispel that expectation with today’s technology capabilities.

Before you can begin to implement generative AI in your CX operations you need to get your data in order. You need someone who understands how you can apply AI to existing data sets and what is required from a governance standpoint to curate the data. Often, much of your data will be in a format that is simply not usable by AI. A data scientist can help you get that data into the appropriate format.

Once the data is in order, and the AI models are set up, you need someone who understands what the feedback means, who can see whether there are issues with the underlying model and who knows how to address those issues. If you don’t have the expertise to understand and analyze the data, that’s a big impediment to implementing your generative AI.

#3 Generative AI consideration: ongoing management

After your generative AI tools are up and running, the job’s not done. You need a CX and AI expert to continuously optimize your system after the pilot and a skilled resource to do analysis and look at where adjustments need to be made to create positive impact.

Many AI platforms are being enhanced on an almost daily basis. With previous technology, you could train your staff to learn the new platform – even if it wasn’t their specific area of expertise. With generative AI, the pace of change is so rapid that it’s akin to requiring your staff to learn a new platform every week.

Beyond just keeping up with the AI, you need to truly understand the inner workings of the solution and the underlying data to determine which levers to pull in order to achieve a specific CX objective.

Generative AI can have big CX benefits … if you get it right.

According to multiple sources, customer experience is the target of most companies’ generative AI initiatives. In a Gartner poll of 2,500 executives, the majority of respondents said customer experience/retention was their primary focus.

Generative AI does have the potential to revolutionize your customer experience – if you have the expertise to implement it strategically. That’s where a third-party with deep expertise in both customer experience and the technology behind it can help you realize the desired business benefits with generative AI.

See how TTEC Digital approaches AI language model optimization with PrecisionLM

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