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It’s not an exaggeration to say AI has officially taken over the workplace…or at least the mindshare of most organizations. According to the 2024 McKinsey Global State of AI survey (May 2024), respondents indicated:
72% of their organizations have adopted AI.
65% are regularly using GenAI at work.
75% predict GenAI will lead to significant or disruptive change in their industries.
GenAI is undoubtedly transforming the way we work. According to Harvard Business Review research (Sep 2024), most business functions and more than 40% of all U.S. work activity can be augmented, automated, or reinvented with GenAI. Work particularly ripe for disruption includes:
Analyzing data: Including cleaning/preparing data, identifying key themes/findings, providing preliminary forecasts, generating reports/summaries, etc.
Creating compelling content: Including email, product descriptions, marketing collateral, social media content, etc.
Providing front-line customer service: Including answering common questions, providing basic troubleshooting, routing cases to appropriate resources, summarizing customer feedback, etc.
This is just the beginning. As the technology continues to advance, more and more “routine” tasks will be automated by GenAI.
What does this mean for Talent Development
In short, organizations need to transform how they acquire, develop, and grow their talent, to succeed in a GenAI world. As GenAI begins to automate more routine tasks, it will free employees to focus on more strategic activities, like:
Planning to address key business problems and opportunities.
Building strong relationships and facilitating collaboration with key stakeholders, partners, and teams.
Managing change and driving the adoption of strategic initiatives.
Evaluating risks and opportunities to make data-driven decisions.
This will transform the skills employees need to succeed in their roles, emphasizing the importance of interpersonal skills like:
Adaptability: Demonstrating flexibility in response to changing priorities, being open to new ideas and perspectives, and effectively managing transitions.
Collaboration: Working with others to achieve shared goals through effective teamwork and mutual support.
Communication/storytelling: Conveying ideas clearly and engagingly, using narratives to inspire, inform, or persuade an audience.
Emotional intelligence: Recognizing, understanding, and managing one's own emotions and those of others, to navigate social complexities and foster positive relationships.
Executive presence: Projecting confidence, charisma, and authority, while inspiring trust and influence across all levels.
Growth mindset: Seeing challenges as opportunities to continuously grow and develop one’s skills and capabilities.
Influence: Shaping the opinions, decisions, and behaviors of others through persuasion, relationship-building, and credibility.
Innovation/creativity: Generating new ideas, thinking outside the box, and developing solutions that challenge conventional thinking.
Problem-solving: Analyzing complex situations, identifying underlying issues, and creating effective strategies to resolve them.
Resilience: Maintaining a positive attitude, staying focused on goals despite obstacles, and persevering through challenges, inspiring peers to do the same.
The 2024 Work Trend Index Annual Report (Microsoft and LinkedIn) shows AI skills will become increasingly important as well, regardless of your profession.
AI fundamentals: Basic knowledge of how AI works, understanding its potential applications and limitations, as well as the ability to use the most popular GenAI tools (e.g., ChatGPT, Gemini, Copilot, etc.)
Data literacy: Reading, understanding, and communicating data insights effectively, to interpret AI-generated analysis and make informed decisions.
Ethical judgment and decision making: Guiding the responsible development and use of AI systems to align with moral principles, ensuring fairness, transparency, and accountability, while minimizing harm and bias.
Prompt engineering: Crafting clear and effective input prompts, to optimize and guide the responses of AI models for desired outcomes.
Tips for developing an AI-ready workforce
How can organizations transform their workforces to excel with these skills? Here are some tips.
Form an “AI Talent Development” team
Many organizations have spun up central or line-of-business teams tasked with identifying and redesigning select business processes and workflows to leverage AI. In addition, it can help to form a Talent Development team (e.g., within your HR or Learning & Development org) focused on identifying and addressing the potential people-related impacts of those workflow changes. Ensure they are a part of or closely liaising with your business process teams, to address everything from redesigning career paths, acquiring the right talent, launching upskilling programs, etc.
Evolve your job roles
Clearly define how responsibilities and skills associated with existing roles, will change based on your AI-evolved workflows. This could involve the creation of new roles and/or restructuring of career paths as well.
Clearly communicate changes to your teams, especially larger-scale ones. Highlight what’s changing, and how those changes will enable work on more strategic activities. Emphasize how you will invest in supporting your teams’ transformation and growth, to align with the evolved roles.
Coordinate with your recruiting teams to update their approaches for finding and acquiring talent that is aligned to the evolved roles as well.
Drive employee engagement
Gallup data shows employee engagement is already low (32% in the US and 23% globally). Resistance to change as roles evolve can impact this even more, especially if there’s a perception AI will negatively impact certain roles.
Use pulse surveys to get baseline engagement readings. Then run them regularly to stay on top of it as changes are rolled out. Address dips before they become major problems.
Don’t forget to focus specifically on the engagement of your managers as well. According to Gallup, 70% of the variance in team engagement is determined by the manager, but only ~30% of managers are engaged themselves. More engaged managers will in turn foster more engaged and productive teams.
Create a culture of learning
As you evolve your job roles, emphasize the importance of upskilling and learning agility. Learning is often seen as something done outside of working hours. However, for such a large transformation, formally allocating time and resources for skill development will reinforce its importance and reassure your workforce you want to invest in bringing them along the AI journey with you.
Try picking a day that’s typically less busy (e.g. Friday afternoon) and encouraging your teams to block time on their calendars for skill development.
Create reward mechanisms for employees who successfully learn new skills and take their transformation to heart. This could be as simple as creating skill badges or communicating success stories. For more important or strategic skills, it could include compensatory rewards (e.g., bonuses, gift cards, day off, etc.)
Leverage “off the shelf” where applicable
There are many 3rd party training providers (e.g., Coursera, Degreed, EdX, Udacity, LinkedIn Learning, Skillshare) that offer training, specializations, and certifications aligned with these transformational skills. Instead of developing training from scratch, use these services to craft curated learning paths aligned with skills critical to your evolved roles. This approach will provide greater cost efficiency and increased agility as AI-related skills rapidly evolve.
Leverage assessments as well (e.g., DiSC, EQ 360, Clifton Strengths, Hogan Personality Inventory, etc.) to help individuals and teams get a sense of where they are today, and how they can focus their development efforts going forward.
Leverage internal expertise
You likely have individuals or teams with significant expertise in the skills discussed earlier. You can launch cross-training initiatives that leverage these internal experts to deliver programs in their areas of expertise. For example:
Product development teams could deliver Design Thinking workshops to build innovation skills. You can create innovation challenges aligned with these as well, giving teams a chance to apply their newly learned skills and potentially generate the next great product idea.
Marketing teams could lead workshops on storytelling.
IT teams could lead training on the effective and ethical use of AI in the workplace.
Sales teams could lead workshops on influence.
In addition to being a cost-effective approach to skill development, this approach can foster collaboration across groups that may not typically work with one another. Your experts can learn from the groups they enable as well, helping them think differently about their areas of expertise.
Facilitate opportunities for intentional practice
These skill development and behavioral changes can’t be achieved through training alone. Your teams need time to practice applying what they learned, to get comfortable incorporating those behaviors into their daily workflows. Create opportunities for them to practice in safe environments. For example:
Challenge your teams to use GenAI tools to create role plays used after their training sessions, allowing teams to practice applying the skills they learned in role-specific ways, and receive AI-generated feedback. In addition to the valuable practice, it will be a great experiential learning activity for your internal experts on using AI.
Create capstone projects/case studies teams can work on after completing relevant training. Incorporate the use of AI as part of the project (e.g., gather data-driven insights, generate ideas/content, etc.). In addition to reinforcing interpersonal skill development, it will enable teams to work with AI more effectively as well.
Create internal stretch assignments or job rotation programs, that allow employees to get out of their comfort zone and work alongside internal experts on different types of opportunities. In addition to expanding skillsets, this can foster collaboration and help teams expand their networks.
Formalize mentorship programs
Mentorship can be a great way to facilitate learning in general, but especially for the types of interpersonal skills that will take on greater importance with AI. Instead of leaving it up to individuals to find effective mentors, build a more formal approach to mentoring, including:
Creating an overall mentoring framework, with associated processes, tools, and templates.
Identifying mentor volunteers with a passion for mentoring and specific expertise with the interpersonal and AI-related skills discussed.
Enabling participants on how to be a good mentor or mentee.
Matching mentees with potential mentors.
Defining, measuring, and tracking progress against success measures and goals.
Good news - there are a variety of 3rd party providers offering SaaS solutions to create and execute effective large-scale mentor programs.
Ready to get started?
Contact us to discuss how we can help you transform your workforce, to align with and take advantage of the AI transformation of your business.
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