A new report by Deloitte reveals that while investment in GenAI is increasing, the clock is ticking to scale and create sustained value. Promising pilots have led to higher investments and rising expectations, however, it has become crucial for GenAI to start providing tangible returns.
According to Deloitte, while organizations recognize the potential of GenAI and continue investing in the technology, they are also encountering significant challenges, including integration issues, a shortage of skilled talent, regulatory pressures, and technical difficulties.
Gathering insights from over 2,700 business and technology leaders across the globe, Deloitte’s State of Generative AI in the Enterprise Q3 report shows that 67% of organizations are increasing investments in GenAI due to strong early value, however, 68% have moved only around one-third (30%) or fewer GenAI experiments into production.
The report also reveals that business leaders are becoming less enthusiastic about GenAI, with the initial fervent excitement shifting toward a more critical evaluation of GenAI’s actual impact on business outcomes.
The interest in GenAI remains “high” or “very high” among senior executives (63%) and board members (53%), however, these numbers are significantly lower compared to the Q1 report, dropping 11 percentage points and 8 percentage points respectively.
Data management remains a crucial factor for successful GenAI deployments. Seventy-five percent of organizations are increasing their budget toward GenAI, according to the Deloitte report. However, unforeseen data-related issues have been exposed, causing 55% of the organizations to avoid certain GenAI use cases.
One of the key findings of the report is that 41% of organizations struggled to define and measure the exact impacts of GenAI efforts. Additionally, only 16% of the organizations reported that they generate reports about the value being created with GenAI.
The challenge in measuring GenAI success often arises from its wide range of use cases, which require a more granular and tailored approach. However, as business leaders become more critical of GenAI, there will likely be a growing emphasis on evaluating the value generated by the technology.
Deloitte recommends defining key performance indicators (KPIs) for each specific use case, including metrics such as efficiency, productivity, and user experience improvements.
The report underscores the main barriers to the successful development and deployment of GenAI include regulatory compliance (36%), difficulty managing risks (30%), and lack of a governance model (29%). Each GenAI use case can also present unique challenges such as novel privacy concerns and protecting new attack surfaces.
To address these challenges, organizations are focusing on establishing new guardrails, educating their workforces, conducting assessments, and building oversight capabilities.
There is also a human element to mitigating some of these risks. “The complex discussions around creating value and managing risk makes it clear to me that we need to keep humans at the center of all this decision-making,” notes Jim Rowan, Applied AI SGO Leader and Principal at Deloitte.
“It is the human stakeholders who impact how applications are conceived and developed, how they are adopted and used, and how they are managed for trust and security. In this, employee upskilling and change management remain indispensable elements of value-driving GenAI programs.”
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Deloitte’s research reveals that companies that rigorously measure performance, responsibly democratize GenAI, and use data as an accelerator rather than a barrier will be better positioned to reap the benefits of GenAI.
However, as highlighted by a recent report by McKinsey, “high performers” are likely to see more challenges with data. These are organizations that are further along in their GenAI adoption journeys and typically allocate a higher share of their budgets to GenAI investments.
While these companies face more challenges, they effectively manage these issues through heightened risk awareness, well-defined mitigation processes, curated learning programs, and clear KPIs to measure GenAI value.
While the journey of adopting GenAI presents significant challenges, it also offers substantial opportunities for those who navigate these hurdles effectively. As the GenAI landscape continues to evolve, strategic foresight and adaptability will be crucial for achieving sustained success.
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