A human-centric approach to AI

Dixa is different. Our customers are different. And, of course, our approach to technology is different. That’s why, when we launched our first bleeding-edge AI features earlier this year, our approach and focus were different from the rest of the industry. 

While other industry leaders focused on software to deflect (one of my least favorite words, ever) customer service queries, Dixa started with a more multifaceted approach. An approach that started with the humans at the center of customer experience. This led us to build a suite of tools that improve experiences for customers, agents, and service leaders. These features do more than improve efficiency, they make life a little easier, a little better, and a little more delightful for humans. 

That’s why today, I’m particularly proud to share more about our vision and philosophy for AI — something that we call our Human + Artificial Intelligence (HAI) approach. 

The choices we make with AI

There’s a lot of doom and gloom predictions about AI. I’ve sat in rooms with CTOs who have detailed their plans for drastic workforce reductions. I’ve talked with CEOs about “when they can fully automate the customer service function.” And, like everyone else, I’ve heard the talking heads on TV threaten mass unemployment and major societal disruption. 

Here’s the thing: that future might be possible. But it’s not inevitable. I don’t even think it’s probable. Humans are still better at solving complex problems. Humans understand fine distinctions. Humans are up to date on current events and emerging trends. And most importantly, humans crave connections with other humans. I’d still rather talk (or chat) with a person in a critical customer support situation. There are times when we want to know that someone else understands our problem and wants to help us fix it. 

And it’s not just that humans are better than AI at some things. We have a choice about how we leverage new technologies and the role they take in society. I think this tweet sums up my stance pretty well:

At Dixa, friendship is our DNA. We’re a company founded by customer service professionals for customer service practitioners. We build tools to make customer service as easy and natural as talking to a friend — because we believe that connections between humans are important. 

Our customers agree. Far and away, the biggest common thread between our customers is that they love their customers. Whether they’re selling pet supplies, meal delivery services, insurance, great sporting gear, or designing bespoke vacations they know that connecting with their customers is critical to their brand. That’s why humans are at the heart of how Dixa looks at AI. 

Tools should make humans better at work

Look, I’m a product and engineering guy — so I’m also trying to understand how AI will affect my job, and the people that I work with everyday. Maybe it’s just me navel-gazing, but one of the most compelling use cases I’ve seen for AI is its application in software development. 

And because software people are generally obsessed with data, we are already seeing some early studies on how AI is affecting developers at work. In a study from GitHub focused on their Copilot software, a program that helps developers write code, they found that developers that used the AI tool were able to complete a benchmark task 55% faster than those that wrote code alone. 

Productivity is important, but as someone who is responsible for the health of my department, not just how much work gets done, the speed gains from AI were definitely not the most exciting finding to me. In addition to becoming more productive and feeling more productive, 60-75% of developers that used Copilot said that they felt more fulfilled by their jobs, were more focused, and could spend more time on satisfying work. 87% said that they spent less mental energy on repetitive tasks. Faster, less mentally exhausting, more fulfilling work — that’s the type of impact that we should be looking for from AI. 

I absolutely want my teams to feel more fulfilled and engaged — and ultimately, I think this is where we’ll see the biggest gains from AI. I believe so wholeheartedly in this that I’ve centered our product strategy on making sure that the humans who use our products benefit from AI and aren’t just marked for replacement by it. Developers aren’t fundamentally different from customer service professionals and they both want tools that help them solve tough problems efficiently. I believe that Dixa will deliver the productivity and quality of work improvements that CS folks need and deserve. 

Designing AI interventions for complex systems

One challenge I’ve always loved about building products at Dixa is that we have a complex system that serves a bunch of different people. We have customers that reach out to business with support questions who want fast, accurate resolutions to their problems. We also have service agents that need tools that help them understand who that customer is, why they’re reaching out, and how to solve their problems. We have service leaders who want to make sure that everything is running smoothly, that quality remains high, and that the cost to serve customers stays low. And finally we have a host of other folks that support the journey, whether they’re developers who maintain the system, QA folks that help with quality and training, content teams who provide knowledge and answers, team leads who manage and develop agents, or data gurus who leverage CS data to support better business decisions. 

That’s another reason that we’ve taken a multi-track approach to how we leverage AI at Dixa. Each of those groups needs a unique set of tools to help them accomplish what they want to do. That’s why we’re bringing multiple AI products to market:

• For customers: Our new natural language chatbot, Mim, ensures that customers get accurate answers to their questions 24/7, in any language. Mim runs on top of your knowledge base, so there’s no set-up, answers are accurate, and even the tone is on brand. Coming later this fall, Mim will also be able to automate a variety of functions like changing order dates, canceling subscriptions, and performing other actions in backend systems. 

• For service agents: Our agent assistant provides a number of useful features to help you across the service journey. From providing conversation summaries, to translation, to writing and grammar improvement on the fly it gives you the power of GPT, right at your fingertips.

• For service leaders: Mim can dramatically reduce service volumes and shorten wait and handling times. Plus, intelligent handovers get agents up to speed quickly when the bot can’t solve the problem on its own. Our agent assistant can improve both productivity and job satisfaction, reducing training time and turnover. Finally, we’re working on new AI tools that allow you to gain more insight into what’s going on in your service organization so that CS becomes a business intelligence center.

I’m really excited about what we’re bringing to our customers today, and, of course, all that we have planned for the future. 

Seize the moment

Microsoft’s CEO Satya Nadella says, “This moment is like when PCs first showed up at work. The beauty of our industry at some level is that it’s not about who has capability, it’s about who can actually exercise that capability and translate it into tangible products.” The tech is here to stay, it’s all about understanding how to harness it and bend it to your greatest advantage. Just like PCs became the go-to tool for knowledge workers, AI will become an essential part of our work routine. But to do that, AI needs to work for workers – not the other way around. 

At Dixa, we believe that we’re giving you the tools you need to make customer service one of your brand’s biggest differentiators. This means leveraging technology to make sure your human resources have what they need to do something that only they can — delight your customers. If you’re interested in how you can leverage AI to make your team better, happier, and yes, more productive, we can help.


Rob Krassowski

Rob is always trying to figure out what makes things tick — or tick better. That curiosity drives him to build products and companies. He writes about product, market, and technology trends at Dixa, where he’s also our Chief Product Officer.

Share this article

Get CX insights, proven strategies, & the latest news in your inbox every month!

You might also enjoy

AI in Customer Service
7 min read

5 metrics to track the impact of AI on your customer service

Read more
AI in Customer Service
7 min read

7 benefits of AI knowledge bases for increasing customer service efficiency

Read more
AI in Customer Service
7 min read

5 ways to boost customer retention with AI and measure it

Read more