Training your people for immediate impact.

Despite the high prioritization of generative AI among executives, many organizations are struggling to progress due to a lack of talent, clear roadmaps, and strategic direction. Investing in AI skills training for employees is crucial for leveraging the full potential of AI technologies and staying competitive in an evolving landscape.

AI is a top strategic priority.

In a recent BCG study, 89% of executives ranked generative AI as a top-three priority in 2024 (cybersecurity and cloud were the other two). Yet 66% of those executives were ambivalent or dissatisfied with their organization's progress on GenAI. They cited three reasons:

1. Lack of talent and skills
2. Unclear AI and GenAI roadmap and opportunities
3. No strategy for AI and GenAI

Another study by Microsoft and LinkedIn of over 31,000 respondents worldwide showed that more than 75% of knowledge workers are using generative AI today (nearly double the figure from six months previous). Yet, while 66% of leaders say they wouldn't hire someone without AI skills, only 25% of organizations say they will offer training to their employees.

We see this as a missed opportunity. In an experiment led by Harvard Business School with BCG consultants studying the impact of GenAI, typical consulting tasks completed with the support of GenAI showed a 12% increase in tasks completed. Speed of task completion increased 25%, and quality of work increased 40%. The greatest impact was seen on below-average performers (over 40% increase), but impact was seen across the board (17% increase in above-average performers).

These technologies will increasingly support so many of our daily tasks: strategic thinking, communication, data analysis, research, and more. The benefits of training your people can provide immediate impact in their day-to-day work.

Why, then, are leaders who see the impact and importance of these technologies choosing to leave the skills development of their workforce to chance? It's likely a combination of the rapid emergence of AI, fear and uncertainty around its impacts, concerns about data security, privacy, and IP risk, plus competing priorities. These are valid concerns, but the reality is that the sooner you can start to train your people, the greater your capacity will be to address these challenges directly.

So what can you do to equip your people with the skills to start leveraging AI more effectively today?

AI is a very broad term and a rapidly developing field. Organizations will increasingly require specialized skills and roles around AI, data science, machine learning, and many related fields. Becoming an AI-driven organization won't happen overnight. However, there are two areas that organizations will benefit from upskilling their people on today.

AI Strategy & Management

Develop perspective on the impact of AI for your organization and the skills to drive effective AI implementation. In the coming weeks we'll share more about how leadership can develop an effective approach. In the meantime, here is a quick teaser on what every leadership team needs to be equipped with to adapt:

1. AI Impact. Understand the impact of AI and how it can be used to transform the way organizations work, improve customer experiences, and drive competitive disruption.
2. AI & Humans. Understand how AI usage impacts the humans that make up your workforce, customers, and communities. Effective rollout of AI programs will depend on it.
3. Data foundations. AI runs on data. Ensure your leaders understand the importance of data and have a base-level understanding of data foundations.
4. Delivering AI value. The AI hype machine is on overdrive. Understand how to identify valuable and feasible AI use cases and translate your experience in delivering digital solutions to AI technologies.
5. Responsible AI. Understand the risks and ethical considerations of AI adoption and develop the policies and governance to ensure responsible usage.

Further reading in the meantime

• McKinsey: A New Future of Work, The race to deploy AI and raise skills in Europe and beyond
• HBR: How AI Affects Our Sense of Self
• Oxford Insights: Organizational AI Readiness Assessment
• BCG: A Guide to AI Governance for Business Leaders

Generative AI Usage

Equip your people to maximize the value they receive from their interactions with generative AI. One of the contributing factors to why organizations aren't training their people is the low barrier to value with these large language models. It doesn't take much to get impressive results. In the early days of ChatGPT, it was astounding to get responses that were clearly different from what any other technology had ever provided.

While the results may be impressive compared to our expectations of previous technologies, the most common critique I hear is that the results are bland, potentially inaccurate, and generally lacking a human level of quality. These are good critiques, but the challenge is that many people stop there. The true value in leveraging generative AI comes when you hold the line on quality and learn how to collaborate with the tools effectively.

Current LLMs, like ChatGPT, are a bit like a junior employee with an encyclopedic memory of every fact, perspective, and opinion ever posted on the internet. They can do amazing things when instructed well, but knowing how to get the best out of them takes learning, persistence, and practice.

Here are a few areas where every organization should be equipping their employees:

1. The art of the possible. Inspire confidence in the opportunity and motivate your people to invest in practicing by demonstrating how others are using GenAI in their work today.
2. Effective prompting. Learn strategies and tools to improve the quality of output you're receiving from every interaction with generative AI.
3. Advanced LLM usage. Develop custom GPTs to perform repeatable tasks, use web browsing, work with multiple modalities (text, voice, image), and use code interpreter for data analysis and technical tasks.
4. AI process augmentation. Understand how to break down jobs into tasks AI can perform and how to effectively use AI to augment your work.
5. Current limitations. Recognize when you should and shouldn't use current LLM capabilities (the "jagged frontier").
6. Responsible AI. Ensure safe usage of sensitive data and understand ethical boundaries of AI usage to guide responsible practice.

Investment in AI continues to increase and we see more practical use cases for GenAI every day. There are an increasing number of practical skills important for employees to have in their toolkits to perform their work as effectively and efficiently as possible. Start training your people to stay ahead of the curve and see the immediate impact in doing so.