As generative AI (GenAI) makes strides across sectors, new opportunities and risks arise in tandem. The latest McKinsey survey findings illuminate how businesses are managing these dual realities: proactively mitigating risks while overhauling workflows to achieve outsized results.
1. Risk Mitigation: A Proactive Approach
Inaccuracy, cybersecurity, and intellectual property are top-of-mind concerns for organisations exploring GenAI. Companies are responding by:
Strengthening Governance: Establishing dedicated internal teams or Centres of Excellence for risk assessment and compliance.
Reviewing AI Outputs: Ensuring that up to 100% of GenAI-generated content undergoes human oversight before being deployed, particularly in sectors like legal and professional services.
Training and Awareness: Investing in continuous staff education to spot potential errors, biases, or misuses of AI outputs early on.
2. The Importance of Workflow Redesign
Rather than adding AI as a side project, the highest-performing organisations treat AI as a strategic driver of transformation, revisiting and redefining business processes. This can mean:
Breaking Down Silos: Aligning IT, operations, and business units behind common objectives.
Reallocating Resources: Shifting talent and budgets to areas where AI can deliver the most impact, rather than adhering to legacy allocations.
Seeking Bottom-Line Impact: Using AI to create measurable improvements in EBIT—an approach that’s especially evident among larger companies.
3. Centralised vs. Distributed Models: Finding the Right Mix
The survey suggests risk & compliance frequently benefit from a centralised governance model, while tech talent and AI adoption may be best handled through hybrid approaches. This means:
Centralisation provides consistent standards and processes, reducing the likelihood of significant errors.
Partial distribution encourages experimentation, enabling teams to tailor AI solutions to specific departmental needs.
4. Driving Sustainable AI Results
Nevertheless, the outlook for India’s AI landscape remains optimistic. Enterprises are investing in scalable ecosystems and agile innovation frameworks to surmount these hurdles. Building robust governance protocols that ensure AI reliability and trustworthiness will be vital for maintaining this momentum and solidifying India’s position at the forefront of Agentic AI development.
Key Takeaway:
Achieving meaningful AI outcomes demands systemic changes—risk assessments, workflow revamps, and balanced governance models. As GenAI’s influence expands, those who adopt a structured, forward-looking approach will be best positioned to thrive.
Author’s Bio
“ Authored by Vineet Baveja, Founder of Conceptualise, a leading authority on digital strategy and innovation. Over the past 20 years, Vineet has guided businesses in deploying cutting-edge solutions that balance opportunity and risk, ensuring growth and resilience in a rapidly changing world.”
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