Integrating The Next Generation Of AI In Your Business To Improve Customer Service And Kill Ticket Backlogs

Think about your favorite in-store or online retailer and how the shopping experience makes you feel. From seasonal swaps to speedy self-checkouts and strategic ad placement - even the most successful retailers fine-tune their strategy while adopting new efficiencies to meet changing consumer trends. The same thinking should be applied to how businesses approach the integration of generative AI, particularly regarding customer engagement.

Companies must be willing to reimagine the way they interact with customers, abandoning prebuilt, complex workflows that CX tools like chatbots depend on, burning manual playbooks designed for CS teams to learn and follow in order to find answers to customer questions, and instead, embrace the benefits of large language model (LLM)-powered AI agents that have proven the ability to automate and *resolve* 90% or more of most customer interactions.

Building Generative AI Into Your Business

Many companies are grappling with the limitations of their current AI 1.0 solutions, as they lack the flexibility and scalability required to keep pace with the rapidly changing landscape. These outdated tools have become stagnant, requiring human assistance to adapt to customer demands, business policies, market trends, or tech advancements.

LLM-powered autonomous AI agents are the way of the future, both from a financial ROI standpoint and for employees as it allows for increased productivity, personalization and empowers developers to focus on business-critical tasks. Brands relying on customer service solutions requiring manual input of static business logic will slowly - but surely - become obsolete.

Generative AI is literally transforming how organizations operate. By leveraging pre-trained ‘agent’ capabilities made possible by LLMs, such as OpenAI’s GPT, tech-first brands are gaining a new competitive edge by increasing efficiency and improving user experiences. Even in its relatively early stage, generative AI has proven applications across customer service, marketing, sales and operations.

Help Wanted: The Need For Prompt Engineers

AI presents a unique opportunity to alleviate pressure on software development teams. Instead of relying solely on their expertise to build ML/AI algorithms from scratch, brands can leverage emerging tools and platforms, such as LLM-powered AI agents, that bring the power of secure, guided, generative AI into customer interactions. This enables brands to shift the focus from clearing ticket backlogs and instead, hone in on optimizing AI agents towards delivering fully-automated resolutions at scale.

Generative AI solutions streamline the development process, providing pre-trained models, libraries and frameworks that accelerate AI implementation. This allows internal developers to focus on higher-level tasks, such as fine-tuning business procedures and policies, addressing complex, technical needs of the business and ensuring ethical AI practices are followed throughout.

While AI tools may ease the burden on internal developers, they also create a growing demand for a new breed of builders - prompt engineers. These professionals play a crucial role in the implementation and customization of AI solutions, ensuring they align with the unique requirements of each business. Although generative AI is constantly teaching itself, the importance of human involvement and prompt engineers in shaping AI technologies, ensures calibration and ethical considerations. Prompt engineers possess the expertise to fine-tune AI models using natural language commands designed to optimize performance and address any challenges or shortcomings. Their ability to quickly adapt to changing business - and customer needs will be instrumental in driving the long-term success of AI 2.0.

Conclusion

The next generation of AI is upon us and businesses must embrace a transformative mindset or risk staying in an olden-age mindset. This revolution is on the same scale as the introduction of the internet, the debut of smartphones, and the availability of cloud computing. Relying on outdated AI programs bolted onto legacy systems is no longer a viable solution. It’s also a dangerous one, as we’ve already seen the ramifications of unvetted ChatGPT use in non-native environments. Instead, companies must be willing to fully reassess and revamp their approach to AI, focusing on its autonomous capabilities to improve customer engagement and generate ideal outcomes 24/7/365 - every time. The future of automation has arrived and the era of AI agents is here to stay.

Adam Evans is a co-founder and CTO of Airkit.ai. He previously was an Entrepreneur in Residence at Morganthaler and co-founded RelateIQ which was purchased by Salesforce. He leads Airkit’s engineering and product team with a unique blend of technical know-how, business savvy, and a strong product vision.