Why Businesses Fail to Harness Generative AI Correctly
Organizations need to consider several factors to get the most out of this exciting new technology
Over the past few years, the interest in artificial intelligence (AI) and the ways it can be harnessed as a tool for businesses has boomed. In fact, it’s estimated that over 50% of companies globally plan to incorporate AI technologies in 2024. That said, research has found that business leaders still have a lot of questions about this emerging technology.
A recent survey showed that 34% of executives know AI has value but are unsure how to harness it for their business and a staggering 98% are overwhelmed by the number of generative AI tools available today. Even though they are unclear on how to use generative AI and which tools would be most effective, many organizations are still rushing to implement the technology. Because of these factors, many businesses are failing to adopt generative AI successfully.
Organizations need to consider several factors to get the most out of this exciting new technology.
How AI Can Be Used as a Strategic Business Tool
There are endless generative AI capabilities and tools available, so it’s important that businesses invest in the right solutions for their specific needs. Organizations looking into the technology must first clearly define the specific use cases they want to enhance and the benefits they want to bring to the end user. If the goal is to improve customer service, for example, then the selected technology needs to be capable of addressing the company’s pain points in that area.
For instance, implementing a generative AI chatbot could help speed up response times and provide support for customers outside of employee working hours. However, it may not be the right tool for managing inquiries that are highly personal or involve legal or regulatory matters. Running a pilot project or proof-of-concept can help validate the feasibility and value of generative AI before scaling the tools across the whole company or offering it to customers.
In addition to being useful for boosting customer experiences, generative AI can also be leveraged to improve internal operations. For example, the technology can automate repetitive and mundane IT operations, meaning businesses can respond to issues in real time. This means problems can be solved faster, with time freed up for teams to use their skills for more complex and strategic decision-making activities.
Common AI Adoption Errors and How to Avoid Them
Generative AI tools are powerful, but their effectiveness depends heavily on how they're applied and the quality of the data they interact with. A common misconception is that businesses can adopt generative AI without fully understanding its capabilities or limitations, which can lead to mismatches between expectations and outcomes. Many organizations rush to implement generative AI without ensuring they have the right data infrastructure, leading to suboptimal results. To avoid this, businesses should first assess whether their data is accurate, relevant, timely and consistent. If it falls short, adjusting the data strategy is crucial. Once a solid data foundation is in place, businesses can more effectively leverage generative AI for the right use cases.
There are several risks associated with rushing into generative AI adoption. For instance, poorly managed generative AI can result in confidential data being exposed to privacy and security vulnerabilities. This can lead to regulatory issues and damage to company reputation and consumer trust. Additionally, leaked data could even help to train a direct competitor’s generative AI implementation.
Another risk is employees having gaps in knowledge about how to work with AI systems. In fact, 30% of digital leaders say gaps in the digital employee experience have impacted company revenue. To ensure a smooth transition, businesses should invest in upskilling their workforce before rushing to adopt generative AI.
Smart Investment in Smart Technologies
Without properly training employees or assessing the compatibility of their data with the tools they invest in, many organizations are missing out on the benefits generative AI can bring to business operations.
Business leaders need to ensure they are thoroughly prepared before embarking on a generative AI venture. This includes having comprehensive, high-quality data, aligning the technology with their overall business goals and developing a well-planned implementation approach. The organizations that do this will be the ones that successfully harness the technology to improve business operations, drive revenue and get ahead of competitors.
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