AI in 2024: Leaders’ Responses and Chatbot Improvements
Navigating AI: Leaders, Data, and the Chatbot Evolution
Chris Jacob, VP of Product at Language I/O, navigates the evolving AI landscape, predicting leaders’ empirical approach, data’s resurgence, and the transformation of chatbots.
In terms of popularity and presence, 2023 was a banner year for generative AI. From boosting productivity to creating written content, the possibilities for these sophisticated tools generated tremendous hype. 2024 will be the year of AI measurement as we look beyond the technical capabilities of Large Language Models (LLMs) and examine how they impact P & L.
Many organizations are counting on AI payoffs, with Forrester’s September 2023 Artificial Intelligence Pulse Survey showing that 62% of companies are experimenting (29%) or expanding (33%) their generative AI strategies next year. I’ve outlined three AI-focused predictions: how leaders will react to AI’s influence, why data will become the star again, and how improvements in chatbot technology will provide a more human experience.
Leaders Are Going to Become More Empirical About AI
AI is rapidly transforming how we live and work, and leaders recognize the need to look beyond the fanfare to make data-driven decisions. In 2024, executive decision-makers will explore how to measure the benefits of AI tools best. Once they’ve determined the metrics to use for those evaluations, they’ll dig deeper into the ROI of generative AI tools to assess their contributions to the organization.
As leaders find ways to gather and leverage the data generated by AI products, we expect to see an increase in enhancements for existing technologies, driving further investments in these tools. According to McKinsey, 40% of organizations are already planning to increase their overall AI investments because of these developments, according to McKinsey research.
These businesses see AI’s value in improving their processes through automating tasks that humans perform to decrease toil, save time, and reduce error. More companies are also capitalizing on AI’s ability to enhance the customer experience by providing personalized content and recommendations. To utilize these AI tools most effectively, more leaders will take that next crucial step beyond watching technical demos and proof of concepts to integrate them deeply into their existing organizational systems.
AI Will Become the Supporting Cast Member, and Data Will Go Back to Being the Star
Generative AI usage has skyrocketed in the last year, with 79% of survey respondents saying they had some exposure to generative AI and nearly a quarter (22%) saying they regularly use it for their work. These numbers indicate that generative AI is becoming table stakes for organizations rather than just a “nice to have” and will become increasingly necessary to stay competitive.
However, leaders should proceed with caution when it comes to AI implementation because generative AI outputs aren’t always accurate — some tests have shown a 3% to 27% likelihood of ChatGPT making things up, for example — and using generative AI without safety guidelines or a strong data set to fill in gaps in the training data could introduce risks to your organization such as presenting misleading information.
Despite these risks, only 21% of organizations that have adopted AI have established policies around how people can use generative AI at work. Those safety guardrails include mandated fact-checking, prohibiting prompting AI with sensitive or proprietary information, and best practices for ethical content creation.
However, organizations that are overly worried about risk and hesitating to harness the power of AI will be left behind as the technology continues to evolve and provide businesses with a competitive advantage.
Remember the adage: Garbage in, garbage out? It applies to LLMs and generative AI, too. Both rely on data to provide outputs, so expect a revitalized emphasis on data quality so outputs generated from training data are as accurate, clean, and reliable as possible. With a strong dataset to draw from and a reliable tuning process, organizations can avoid the pitfalls of inaccurate outputs.
See More: Leveraging AI Integration to Improve Chatbots & Business Value
AI Chatbots Are Packing Their Bags and Moving Away From Uncanny Valley
Let’s visit the Uncanny Valley, where technology and humanity don’t quite meet. This in-between space both fascinates and repels people, and it is where AI currently resides. LLMs are great at mimicking humans, but when they stumble, it’s apparent that they are parroting back to what they think a person would say. It’s almost but not completely lifelike, “living” in a space between human and almost-human, which can be extremely off-putting for some actual humans.
Regarding critical consumer touchpoints like customer service bots, the margin for error is incredibly small. That slightly repellant Uncanny Valley experience can quickly derail an otherwise smooth transaction. However, that Uncanny Valley gap will close in the coming years as we perfect chatbots’ communication abilities to the point where they’re virtually indistinguishable from actual humans. This perfection, however, may not manifest the way people might think.
We’ll likely compare AI’s efficacy to the “perfect” human response, but what constitutes a perfect response? Three talented translators handed the same text would inevitably produce three excellent translations with differing nuances and verbiage. All three could be “perfect” translations, but they wouldn’t match exactly. It won’t be long before we see similar outputs from AI. It may not be the perfect output, but it will be a perfect output that provides context and information equal to an acceptable human response. Defining and measuring how well chatbots communicate with customers will be key in 2024.
AI helps chatbots communicate better with customers, but communication is just one piece of the puzzle. Customers are looking for outcomes from their chatbot interactions. According to recent Gartner research of customers who used a chatbot in their last customer service interaction, only 25% said they would use a chatbot again. We could conclude from this number that chatbots’ current capabilities don’t quite measure up for many users.
AI can help make workers’ lives easier and more efficient while also improving customer experience; however, organizations have some work to do to safely incorporate proprietary data into the process to drive results for both the customer and the company. The stakes are high, but responsible AI usage will enhance teams’ processes and productivity, benefiting organizations, end-users, and bottom lines.
I see 2024 as AI’s year of reckoning. ROI will be measured, and the results will decide AI’s organizational fate. I anticipate the continued improvements and evolution of this technology will ultimately lead to widespread adoption and a world of business use cases we’ve only begun to imagine.
How will AI reshape your business in 2024? What challenges do you foresee? Let us know on Facebook, X, and LinkedIn. We’d love to hear from you!
Image Source: Shutterstock
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