The coming AI revolution: How leaders will harness its power in 2024

2023 represented a breakthrough year for generative AI, which gained immense popularity for enhancing productivity through instant content creation based on user inputs. However, in 2024, organizations must shift from marveling at generative AI's dazzling technical capabilities to rigorously evaluating its tangible business impact and risk.

Organizations eagerly anticipate AI's transformative potential. Forrester's September 2023 Artificial Intelligence Pulse Survey revealed that most companies are evolving in their approach to AI. More than a quarter are experimenting with the technology, while 33 percent are expanding their existing efforts, the survey found. In light of this heightened interest, here are three critical AI-centric predictions for the coming year:

Prediction 1: Leaders Embrace Data-Driven AI Decisions

Amidst the rapid transformation brought about by AI, leaders are seeking a data-driven approach to evaluate its impact. In 2024, executives will delve into measuring the benefits of AI tools, establishing metrics and assessing the ROI of generative AI. This data-driven approach will fuel further enhancements to AI technologies, driving increased investments in these tools. According to McKinsey research, 40 percent of organizations plan to ramp up their AI investments due to these developments.

Businesses recognize AI's potential to streamline processes through automation, reducing human effort, saving time, and minimizing errors. Additionally, AI's ability to enhance customer experiences through personalized content and recommendations is gaining traction. More leaders will take the next crucial step beyond creating technical demos and proof of concepts to deeply integrate LLms into their existing organizational systems, and as they do, they’ll implement new measurement systems to be able to confirm which applications are having a positive impact on business operations.

Prediction 2: AI as a Supporting Actor, Data as the Star

While generative AI use has gained significant traction over the last year -- 79 percent of survey respondents indicated exposure and 22 percent used it daily -- leaders must exercise caution when implementing generative AI due to the potential for inaccurate outputs.

Remember the old 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 any 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.

By leveraging unique and proprietary data to adapt LLMs, organizations will be able to set themselves apart from the ever-growing number of implementations that are using the same base LLM models. To fully realize the benefit of the technology and stand out from the field, companies will need to explore how their datasets can enhance an LLM’s capabilities.

Prediction 3: AI Chatbots Emerge from the Uncanny Valley

Current AI chatbots often reside in the uncanny valley, where technology closely mimics human interaction but still falls short of being genuinely lifelike. This can lead to unsettling user interactions, especially in critical customer service scenarios.

In 2024, we expect significant improvements in chatbots' communication abilities, enabling them to interact with users more naturally and engagingly. However, perfection is not the goal; instead, the focus should be on achieving a level of communication that is effective, informative and achieves the same outcome as a human response.

Defining and measuring chatbot effectiveness is crucial for the future. Organizations should consider metrics such as customer satisfaction, resolution rates and the ability to handle complex inquiries. Additionally, chatbots should also be integrated into the agents workflow (e.g integrated to the CRM), to not change the way agents operate.

AI is poised for a significant transformation in 2024 when organizations shift from hype and experimentation to a more data-driven and strategic approach to AI adoption. Leaders will prioritize measuring ROI, ensuring data quality and improving chatbot communication quality. Organizations that successfully navigate these challenges will reap the benefits of AI, enhancing team productivity, improving customer experience and ultimately driving business growth.

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Chris Jacob is Chief Product Officer at Language I/O. He joined the company in 2021 after experiencing firsthand the difficulties of supporting a global product with a largely monolingual support team. His time on the road presenting technical concepts using machine translation showed him the need for a translation service that understands the complexities of industry-specific jargon.