Empowering Business Leaders: Key Takeaways from "The C Suite's Guide to Generative AI" Webinar
I recently had the pleasure of presenting "The C-Suite's Guide to Generative AI" with Deltek. In this webinar we explored the potential of generative AI for business leaders delving into how AI can improve functions like sales and marketing and outlining steps to prepare organizations for adoption. This blog captures the essence of that presentation providing strategic insights and a practical framework to help C-suite executives effectively leverage generative AI technologies.
Quantifying the AI Opportunity
By now most business leaders are well acquainted with the opportunities of GenAI for increasing productivity and shaping their creative processes. To put this in numbers studies currently estimate the productivity boosts of AI ranging between 2.8 - 4.7% with potential revenue generation between $200bn - $340bn. As in every discussion these numbers need to be put into context. AI develops rapidly and as technology advances these numbers may shift as well. Yet this technological advancement opens plenty of opportunities for C-suite executives to drive strategic innovations and operational efficiencies - but some lines of business will be affected more than others.
Finding the Edge: Marketing and Sales
Marketing and sales are generally pinpointed as the areas with the highest potential for generative AI integration based on two key metrics: impact as measured in a) functional spend and b) cost savings.
Source: McKinsey & Co, Economic potential of generative AI, 2023
The text-heavy nature of marketing and sales functions lends itself particularly well to augmentation through large language models (LLMs). AI can augment these functions by personalizing customer interactions optimizing marketing campaigns in real-time and generating predictive insights that lead to more effective sales strategies. For instance AI-powered analytics can identify trends and customer preferences allowing companies to tailor their offerings more precisely enhancing customer satisfaction and loyalty.
But to get AI adoption right there are two key areas to focus on:
Building a Framework for AI Readiness
Adopting AI within an organization requires a clear framework that demystifies AI technologies identifies relevant use cases and assesses existing capabilities and constraints.
Last year when interest in GenAI was at its very inception Deltek and I described a framework highlighting the key steps for GenAI adoption. One year on we find that executives clearly understand GenAI's potential and opportunities. By extension today's focus seems to have shifted towards identifying clear use cases and piloting projects. From most of the conversations I've been having with clients globally a number of key success factors play a key role in determining the success of AI initiatives. These typically include:
- Establishing clear objectives: Defining precise business objectives and aligning AI initiatives accordingly.
- Unifying efforts across the organization: Ensuring that AI projects are harmonized across the organization bridging gaps between technical and non-technical teams.
- Goal and strategy distinction: Maintaining a clear distinction between overarching goals and the strategic roadmap focusing on building essential prerequisites such as data infrastructure and nurturing a supportive organizational culture.
Encouraging an AI-Driven Culture
However the irony of AI adoption is that its success within any organization hinges on cultural readiness rather than merely technological maturity. In other words it would be hard to imagine an organization successfully adopting a technology unless its users ultimately accept it. Yet the business case is clear: an AI and data-driven culture enhances profitability and productivity by 6% and 5%, respectively. However cultivating such a culture presents numerous challenges.
Despite the clear benefits only 25% of employees feel confident in their AI and data literacy skills. This gap underscores the necessity for comprehensive training and development programs aimed at enhancing data literacy across the organization. Such initiatives ensure that all team members not just data specialists can effectively interact with AI tools and interpret AI-driven insights. A few initiatives can help drive an AI culture across organizations depending on the size and number of workers.
- Small Businesses (1-50 workers): This should include practical hands-on training sessions that enable employees to interact directly with AI technologies helping demystify AI and build foundational skills.
- Medium-sized Businesses (50-150 workers): Organizing regular cross-functional meetings involving AI/IT departments facilitates better understanding and integration of AI applications.
- Large Businesses (150+ workers): Establishing AI Academies or Task Forces that operate across different segments of the business can be effective for strategic AI education and implementation.
Driving AI Integration: Insights from Waterstons' Strategic Approach
Lora Barclay Business Systems Lead at UK consulting firm Waterstons joined me on the webinar to present real-world examples of how firms are working to integrate generative AI.
In the past 18 months Waterstons has nominated an executive 'AI business sponsor' leading an internal cross-functional workgroup focused on developing AI strategy across all functions of their business. This sponsor ensures all research and development aligns with a business use case or delivers against business goals - a key success factor. So far the team has run two hackathons and developed a 'Service Order AI Assistant' prototype (reducing the time it takes to create a client proposal) plus offered external client workshops and training to support their customers in using generative AI themselves.
Deltek and AI
Deltek's VP of Product Management Bret Tushaus (who also joined me on the webinar) commented "There are huge opportunities beyond what we've already done with both traditional and generative AI.
At Deltek we see generative AI and the capabilities around it as a mechanism through which our customers can have a conversation with their ERP software to make their organizations even smarter in terms of how they use data to make decisions plan and deliver future projects.
Earlier this year Deltek launched Dela an AI-powered assistant incorporated across our product portfolio that helps our customers with everything from automating tasks to extracting insights from complex data or anticipating resource needs."
Conclusion
GenAI adoption is now in full swing. As companies venture further into exploring its use their emphasis will increasingly shift towards creating robust frameworks that enhance technological capabilities while addressing ethical cultural and operational challenges. This journey toward AI readiness will involve continuous learning and adaptation to stay ahead and maintain competitive advantage.
Missed The C-Suite's Guide to Generative AI webinar? You can watch it here.
About the Author
Walter Pasquarelli is an expert advisor on AI strategy, data governance, and digital transformation, advising Google, Meta, Microsoft, and presidencies and governments internationally.
Leading advisory and editorial programs at The Economist Group, Walter operated at the forefront of technological innovation, shaping policy and business perception of emerging technologies. He led the development of the first globally focused "AI Index", benchmarking countries' readiness to uptake emerging technologies across key industries and markets.
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