It’s 2024. Time to start executing on your gen AI strategy

As companies make their way up the generative AI learning curve, we offer guidance for executing a strategy that delivers real value.

Generative AI had quite a year in 2023—and so did the enterprises learning to adopt it. Companies are slowly but surely making progress on the generative AI learning curve. They’re assembling use case libraries, identifying strategic partners, strengthening the data foundation and defining policies and controls. Chief data officers everywhere are thrilled.

Now, though, it’s time to move generative AI from proof of concept to production. Here are a few ways to ensure you can successfully execute on your gen AI strategy.

Motivate internal leaders to align with common goals

The noise level over generative AI ideas has been deafening (think replacement of marketing or accounting). To quiet things down, businesses should align leaders’ expectations around corporate goals. Weed out use cases that are too expensive to scale or get into production. Instead, double-down on efforts that advance your company’s business objectives.

If productivity is an integral part of your company’s growth strategy, then prioritize generative AI-driven applications that boost employee output.

Leadership plays a pivotal role in motivating and ensuring alignment. Some businesses establish dedicated C-suite posts for AI. Others designate chief people officers to serve as champions.

One large company has formed an advisory council of senior leaders who ensure each business function embraces generative AI. By checking the pulse of generative AI within each department, the board hopes to both gain insight into AI’s impact on business functions and defuse workplace unease about the technology.

Organizational change management professionals can play an important role here, complementing the work of internal councils by helping businesses quell workforce fears.

Convert concerns about generative AI into better risk management

Generative AI-related risk remains top-of-mind for organizations. And for good reason: Security and data access, for example, or inaccurate outcomes are legitimate concerns, as are intellectual property and copyright violations, particularly in industries such as media and entertainment.

The smart strategic move, however, is to keep advancing pilots and proofs of concept, and then mitigate risk as you go.

Instead of letting ethics and compliance concerns hold back your organization, use them to strengthen your policies and governance.

We’re beginning to see a greater interest in guardrails as companies forge ahead in their generative AI efforts. When Google introduced its multimodal AI model Gemini in December 2023, CEO Sundar Pichai emphasized the need to build safeguards and collaborate with governments to address risks.

Earlier in 2023, Google introduced Google-Extended, a tool that lets websites and content creators appear in Google searches and opt out of their content being scraped for LLM training by tools like Bard.

The upshot? Trust and safety can be part of the discussion while generative AI continues to find its way into the enterprise.

Tackle FOMO head-on

Generative AI’s move into the mainstream has brought with it plenty of fear of missing out. Enterprises worry about rivals’ use of LLMs. Employees question generative AI’s impact on their jobs. More than one-third of professionals are anxious about falling behind on AI at work, and rank-and-file workers aren’t the only ones concerned about their future: 49% of CEOs surveyed say most or all of their jobs should be completely automated or replaced by AI. 

Tackling generative AI FOMO from the bottom up is critical. Our own research reveals 90% of jobs could experience some disruption over the next 10 years. Conducting open, productive assessments is a key task for companies. Forward-thinking organizations are encouraging employees to enrich their job profiles by assessing which skill sets are core to their jobs and which can benefit from AI-driven efficiencies.

Keep a close watch on the AI landscape−not just the tech leaders

Tech businesses get the lion’s share of attention when it comes to AI. But plenty of industry-specific vendors are also making waves.

Our recommendation is to track the players in your industry as well as the tech giants. Companies garnering investors’ attention for niche AI applications range from Jasper for marketing and Biomatter for health and sustainable manufacturing applications, to PerplexityAI in search. Don’t miss the small players in your industry. They might just become the leaders.

To learn more, read our report, “New work, new world” on the economics of generative AI.