Organizations Embracing Gen AI for Future Value Creation
Organizations are starting to make strategic organizational changes designed to harness the potential of generative AI (gen AI) for future value creation. Large companies are at the forefront of this transformation, driving bottom-line impact through the deployment of gen AI. According to the latest McKinsey Global Survey on AI, companies are redesigning workflows, appointing senior leaders to oversee AI governance, and actively mitigating gen-AI-related risks. The momentum around the use of AI, including gen AI and analytical AI, is rapidly increasing, with more than three-quarters of organizations now leveraging AI in at least one business function.
How Companies Organize Gen AI Deployment
CEOs playing a crucial role in overseeing AI governance have shown a strong correlation with higher self-reported bottom-line impact from gen AI use, especially in larger organizations. The redesign of workflows has emerged as a key driver of EBIT impact from gen AI deployment, with organizations reshaping their processes to accommodate gen AI. Centralizing elements of AI deployment, such as risk and compliance, data governance, and tech talent, is a common practice, with different models being utilized based on organizational needs.
Organizations Vary in Monitoring Gen AI Outputs
Organizations are adopting different approaches to monitoring gen AI outputs, with some reviewing all content created by gen AI before use, while others review a smaller percentage of outputs. The focus on managing gen-AI-related risks has increased, with organizations actively addressing issues related to inaccuracy, cybersecurity, and intellectual property infringement.
Best Practices for Adoption and Scaling of Gen AI
While most organizations are yet to realize organization-wide, bottom-line impact from gen AI, the adoption and scaling practices play a crucial role in enabling value creation. Tracking well-defined KPIs for gen AI solutions and establishing clear roadmaps for adoption are key practices that drive EBIT impact. Larger organizations are leading the way in implementing these practices, with a focus on building awareness, capability training, and fostering trust in gen AI solutions.
AI Shifting the Skills Needed
Organizations are witnessing a shift in the skills required for AI-related roles, with a growing demand for data scientists, machine learning engineers, and AI compliance specialists. Reskilling the workforce is becoming a common practice, with organizations investing in training programs to equip employees with AI capabilities. The survey also highlights the challenges in hiring for AI-related roles, with data scientists remaining in high demand.
AI Use Continues to Climb
The reported use of AI has seen a significant increase, with more organizations leveraging AI in multiple business functions. Gen AI deployment is also on the rise, particularly in areas such as marketing and sales, product development, and IT. Organizations are experimenting with various modalities of gen AI outputs, with a focus on creating text, images, and computer code. While organizations are seeing value creation within business units using gen AI, enterprise-wide impact on EBIT is yet to be fully realized.
About the Research
The online survey conducted by McKinsey gathered responses from 1,491 participants across 101 nations. The data, weighted by global GDP contribution, provides insights into the current state of AI adoption and the organizational changes required for successful gen AI deployment.
FAQ
Q: What are the key drivers of bottom-line impact from gen AI deployment?
A: CEO oversight of AI governance, workflow redesign, and effective risk mitigation strategies are key drivers of bottom-line impact from gen AI deployment.
Q: How are organizations structuring their AI deployment efforts?
A: Organizations are selectively centralizing elements such as risk and compliance, data governance, and tech talent, based on their specific needs and capabilities.
Q: What are the challenges in hiring for AI-related roles?
A: Data scientists, machine learning engineers, and AI compliance specialists are in high demand, posing challenges for organizations in filling these roles.
Conclusion
Organizations are at the forefront of leveraging gen AI for future value creation, with large companies leading the way in organizational changes and strategic deployment of AI. The adoption of gen AI continues to climb, with a focus on driving bottom-line impact through effective governance, workflow redesign, and risk mitigation. As organizations navigate the evolving landscape of AI technologies, reskilling the workforce and implementing best practices for adoption and scaling will be key to unlocking the full potential of gen AI.
