Generative AI has the power to transform virtually every business sector. It has been widely adopted in software development, content creation, customer service and more. Use cases have emerged in industries ranging from healthcare to manufacturing to education. It enables unprecedented levels of efficiency and accuracy and provides insights that drive innovation.
Not surprisingly, organizations are investing heavily in GenAI technology. In a new KPMG survey, 97 percent of business leaders said they plan to invest in GenAI over the next 12 months. Research firm MarketsandMarkets expects the global AI industry to see a compound annual growth rate of 36.8 percent through 2030.
In a 2020 article, Infosys Knowledge Institute predicted that organizations using AI will increase profits by 38 percent, adding $14 trillion in value by 2035. However, AI initiatives often fail to meet expectations. In a Gartner survey conducted in the third quarter of 2023, just 10 percent of organizations had fully implemented a GenAI solution. Another 45 percent were experimenting with the technology.
Entering the ‘Trough of Disillusionment’
According to Gartner’s 2023 Hype Cycle for Emerging Technologies, GenAI had already reached the Peak of Inflated Expectations by August 2023 — an incredibly rapid ascent. Once past the peak, it will quickly plummet into the Trough of Disillusionment, where it will linger for two years or more before reaching the Slope of Enlightenment. That doesn’t mean that GenAI won’t deliver value during this time. It simply means that organizations must take a pragmatic approach to GenAI adoption.
Realizing the business benefits of GenAI requires a well-thought-out strategy. It starts by defining key performance indicators (KPIs) early in the planning process and estimating GenAI’s impact on each KPI. This will enable the organization to develop an action plan, with rigorous assessment at every step.
Organizations must also consider the potential risks of GenAI. The deployment strategy should build in controls for data quality, model integrity, privacy and security.
GenAI Adoption Challenges
One of the biggest challenges that organizations face is a lack of expertise in GenAI technology. In a recent Skillsoft study, 43 percent of IT leaders rated their team’s AI and machine learning (ML) skills as “low.” Almost one-third (30 percent) said they are having the greatest difficulty hiring staff with AI and ML expertise. A recent Deloitte survey found that 31 percent of organizations ranked AI skills deficiencies among their top 3 concerns.
A reluctance to retool business processes can also derail AI initiatives. To be effective, AI must be fully integrated into business processes that have been optimized for automation. However, business leaders often cling to existing workflows, viewing AI as too expensive, disruptive and resource-draining.
“AI washing” is another major problem. Some companies are making false or misleading claims that their products use AI in order to capitalize on the latest industry hype. In reality, most GenAI solutions are still in the beta testing phase. AI washing erodes confidence in the technology.
How Technologent Can Help
Technologent has developed a practice dedicated to GenAI to help organizations overcome these challenges. It draws upon our expertise in automation, cloud, data management and cybersecurity, blending these disciplines into an end-to-end strategy.
Our GenAI model incorporates people, processes, tools, knowledge and culture. These components work together to increase efficiency, improve business processes, accelerate deployment, drive continuous improvement and manage ROI. At the center lies IT automation, ensuring that physical, virtual and digital platforms work together to deliver the desired business results.
GenAI can be transformative, but organizations face significant hurdles in capitalizing on its benefits. Let Technologent help you implement a GenAI solution that is reliable, responsible and secure.
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