What’s our plan for Generative AI? If you're not asking, you're already behind.

Generative AI is a transformative force that’s reshaping industries and how we approach work. The question every CEO, AI leader, and decision-maker is now asking: What’s our plan for Generative AI? If you're not asking, you're already behind.

Understanding Generative AI

At its core, Generative AI refers to deep learning models designed to produce human-like responses based on prompts. These models, such as Large Language Models (LLMs), power applications like ChatGPT, Bard, and Midjourney. They interpret text, generate natural language, and even produce images or code. But beyond the technicalities, Generative AI is about much more than just words on a page—it’s about creating new ways to solve problems and unlock efficiencies.

What Can Generative AI Do?

From document creation and code generation to brainstorming sessions and customer service chatbots, the capabilities of Generative AI are vast. It's not just performing repetitive tasks; it's about doing them better, faster, and more efficiently than traditional methods.

The Opportunity: Productivity and Beyond

Generative AI will become a key productivity driver across sectors. The copilot model—where AI assists human workers—is rapidly becoming the norm. For example, AI can summarize lengthy reports, generate insights from vast datasets, and even provide dynamic recommendations for shopping or financial services.

In fact, according to an Accenture study, up to 40% of working hours could be impacted by LLMs like GPT-4 [oai_citation:4,1728318987839.pdf](file-service://file-ozaPs0aBKxSzvfgoaOvxYkKO). Imagine the productivity gains when AI handles the mundane, allowing human creativity to flourish.

Driving New Revenue Streams

Generative AI doesn’t just enhance productivity—it opens doors to new revenue streams. Companies can leverage AI for personalization and recommendation engines, automated content generation, and even more complex activities like financial analysis or medical diagnosis.

For example:

- Retail can offer conversational shopping experiences.

- Healthcare can automate parts of medical records handling and claims processing.

- Banking can analyze customer data for risk assessment or generate insights for investment analysis.

With these use cases emerging across industries, the possibilities are endless. But success lies in choosing the right use cases for your business. Focus on value and feasibility to ensure a higher rate of success in AI initiatives.

The Risks: What You Need to Know

Every new technology comes with risks, and Generative AI is no different. Two categories of risks you need to be aware of are disruption risks and technology risks.

Think back to how the internet created new market leaders. Web 1.0 birthed search giants, and Web 2.0 brought about social media dominance. Generative AI is Web 3.0 in its ability to revolutionize industries. Companies that ignore it will be left behind, outpaced by more efficient and AI-driven competitors.

For instance, a study found that customer service agents using ChatGPT were 14% more productive than those who didn’t. This improvement wasn’t just in speed—it also elevated the performance of less experienced workers. Imagine the cost savings and operational improvements if your AI could handle customer service, marketing, and even parts of research and development.

Generative AI is also a double-edged sword. If left unchecked, it can leak confidential information, produce incorrect data, or go off-topic in alarming ways. For example, we’ve already seen Samsung employees unintentionally leak proprietary data into ChatGPT [oai_citation:2,1728318987839.pdf](file-service://file-ozaPs0aBKxSzvfgoaOvxYkKO). And while AI hallucinations might sound amusing, they can result in misinformation, as evidenced by ChatGPT’s incorrect responses about world records [oai_citation:1,1728318987839.pdf](file-service://file-ozaPs0aBKxSzvfgoaOvxYkKO).

The lesson here: Governance matters. Without strong oversight, your AI could embarrass you in ways you didn’t anticipate, leading to serious PR issues.

Realizing Value from Generative AI

For companies that embrace Generative AI, the return on investment is tangible. Whether it’s improving internal efficiencies by automating back-office tasks or enhancing customer experiences through dynamic AI interactions, Generative AI creates value in nearly every department.

Not every organization is ready to dive into full-scale Generative AI use. First, you need to understand where you are on the AI Maturity Curve:

- Low Maturity: Start with internally-focused, productivity-enhancing use cases, which have lower risks and higher feasibility.

- Medium Maturity: Augment existing AI use cases by analyzing text data to extract new features and enhance predictive models.

- High Maturity: For companies ready to lead, develop new, public-facing use cases that require rigorous governance and security measures.

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This article captures the major points about leveraging Generative AI while providing a strategic perspective.