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The Talent Implications of Generative AI

      Artificial intelligence (AI) continues to advance at a rapid pace, bringing new capabilities that promise to transform many industries. One area seeing significant progress is generative AI – systems that can generate new content, like text, images, and video, based on example data they are trained on.

        As these generative models become more sophisticated and widely deployed, what could it mean for talents and skills in creative and knowledge-based fields? In this post, we’ll explore some of the talent implications as generative AI progresses.

        Software Engineering – Massive Productivity Gains But Need for Upskilling

        Generative AI promises major productivity improvements in software engineering. Systems like GitHub’s Copilot can suggest entire lines and blocks of code to engineers as they work based on deep learning across millions of open source projects.

          In a recent survey, nearly two-thirds of software engineers said they expect productivity gains of 20% or more from AI coding assistants like these. And 16% already report achieving gains of that magnitude. This means engineers can get more done in less time, accelerate delivery of digital projects, and focus their efforts on higher-value and more rewarding tasks. But it also means the bar will be raised on what skills are needed to differentiate.

        About 39% of software companies already cite lack of technical skills as their biggest talent barrier. So while AI assistants boost output, companies will need to double down on upskilling talent as well. Understanding exactly how and when to leverage generative code suggestions takes discernment – putting foundational software fluency at a premium.

      Architecting complex systems will also become more important than writing routine code. And skills like critical thinking, communication, and translating coding into business impact will be differentiators. Companies that invest early in levelling up talent in these areas can gain a competitive edge.

Content Creation – Higher Output but Greater Need for Curation

        Generative AI is also making major waves in content creation. Tools like Anthropic’s Claude can generate entire blog posts, marketing copy, emails, and more based on a few prompts. This allows marketing and creative teams to be exponentially more productive.

         But as with code, generating content is just one piece. Knowing what content to generate, how to feed the AI with strategic prompts and direction, evaluating the output, and refining it into something publication-worthy is where human skills remain essential.

         This means roles focused on content strategy, critical thinking, and quality control will become more prominent. Creative fields like graphic design may also see a boost as generative tools increase the volume of content that needs visual styling.

Customer Service and Sales – Smarter Self-Service

         Generative AI in customer service tools can parse and respond to routine customer queries. This will enable smarter self-service options and free up human reps for the more complex and relationship-oriented inquiries.

             According to McKinsey, generative AI could automate 30-50% of B2C customer interactions within 5-10 years. On the sales side, new quoting and proposal tools will allow small businesses and consumers to get custom packages faster than ever. This increases efficiency for both buyers and sellers.

          As interactions scale, success will center on using AI to personalize self-service while focusing human effort on building connections. Navigating this balance demands talents like empathy, creative problem solving, and change management.

The Path Ahead

          As this brief overview illustrates, generative AI will shape demand for talents in software, marketing, creative fields, and customer roles. While raising productivity, it also raises the bar on the skills needed to differentiate.

          This makes sourcing technical core competencies tablestakes. But to fully leverage AI’s potential, the differentiating talents will be ones bringing strategy, discernment, and creative direction. Companies that realize this early and invest in upskilling along these lines will have the first mover advantage.

            The coming wave of generative AI brings enormous opportunity. But realizing its full promise and avoiding displacement will require matching its advances with talent development. By taking this dual-pronged approach, progressive firms can ride the crest ahead.

Conclusion

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