The Generative AI Competency Framework By The Morning Grind

Executive Summary: I have designed this Generative AI Competency Framework to articulate the display of key competency levels across businesses. Organizations can then define the skills gaps and mindset shifts needed to move their wider employee base from one competency level to the next.

With generative AI growing in urgency as a skill and mindset needed for organizations to survive, much less thrive, L&D teams must analyze and determine the situation at their own organization. This framework serves as a tool to enable businesses to map out the current gen AI skills levels among their teams, in order to take the steps needed for business value creation with gen AI strategy.

You can use this framework as an analysis tool to determine how developed gen AI competency is as a whole across your organization, what the skill gaps are and how quickly different employee subsets are moving up the curve. Identifying where your organization stands on this pathway will enable you to design the right interventions to build the necessary level of gen AI competency.

Do note that this is a framework for people who are not in IT, engineering, coding or other adjacent roles. The framework’s focus is on the intersection of commercial and business acumen with AI, and is meant for roles outside of tech and IT.

I break down the competency framework into 4 distinct layers, going from the most foundational layer of skills and mindsets in generative AI to the most complex layer which involves business value creation. I also discuss how learning interventions by L&D teams might look like at each of these levels.?

1. Foundational: This is the level where employees are expected to have a basic understanding of the foundational concepts of generative AI, as well as know the key terminologies that are constantly used and discussed in the knowledge domain. This level should be easy for employees to achieve as the information is available in the public domain.

2. Intermediate: To achieve this competency, employees are expected to understand how the concepts are applied in their own business, in their industry and in the marketplace. While some of this knowledge is available in the public domain, there is still knowledge asymmetry and requires intervention from L&D teams to design learning pathways, access to experts, case studies, use cases and internal tribal knowledge to bridge the knowledge gap.

3. Proficient: At this level, we begin to draw a distinction in our expectations of employees across different seniority levels. We expect employees at this competency to be able to use AI tools proficiently to solve high priority business problems. More senior leaders should be able to think about how gen AI can transform business processes through automation as well as enhance the employee and customer experience.?Here, a learning culture and practice is closely tied to knowledge sharing and collaborative practices. Formal training is needed to enable employees to adopt new tools and processes. “How-to” sessions and guides will be extremely useful.? This, however, should be supported by internal experts and champions who are openly sharing how they apply gen AI in their work and the benefits these actions have created.?

4. Business Impact: I wanted to define another level beyond Proficient due to the commercial value potential of generative AI. Beyond just having generative AI skills, this competency level is defined by employees’ ability to drive business value creation. We look at how business unit leaders build gen AI into key business goals and how employees translate these goals into actionable plans.

In order to drive AI mindsets and transformation, adoption champions play a key role in ensuring knowledge transfer happens across the organization. It will also be meaningful and useful to adopt an ROI measurement framework - employees will be more open to AI upon seeing the real business value it creates for the business.?

Foundational??

Core Principle: Understand key foundational concepts of generative AI and the key terminologies

Display of Competency

1. Employees understand key basic? concepts and show familiarity with key terms used in Gen AI such as LLMs, deep learning, chatbots etc
2. Employees display a basic understanding of the technological principles supporting gen AI functionalities
3. All employees possess a high-level understanding of use cases of gen AI across different industries and the business landscape in general. For example, employees know that gen AI is widely used for fraud detection in banking and content generation in marketing
4. Employees possess a high-level understanding of how gen AI is used in their own industry as well as know the common use cases?
5. Employees should possess a high-level understanding the ethical ramifications of gen AI on businesses, companies and employees in general

Employee level:

This is relevant for all employee levels across functions and seniority tiers.

Intermediate???

Core Principle: Moving beyond the understanding of concepts to understand how they are applied in the business

Display of Competency:

1. Display an understanding of business implications and impact with in-depth knowledge of use cases of gen AI in the industry and adjacent industries e.g. how gen AI is applied, the specific tools used, the results
2. Have a deep knowledge of how gen AI is applied in the own organization, and what are other potential growth areas
3. Research and understand how gen AI is being used by competitors, going deep into understanding the tools that they are leveraging
4. Experiment with using AI tools / chatbots like Chat-GPT and Co-pilot to streamline tasks and enhance personal productivity
5. Possess an in-depth understanding of the ethical implications of gen AI for the business.

Employee level:

This is relevant for all employee levels across functions and seniority tiers.

Proficient??

Core Principle: Employees are adept at applying AI tools confidently and implementing AI solutions to solve business problems that have been clearly defined and prioritized.

Display of Competency broken down across levels:

Senior Executives:

1. Identify the core areas of the organization (processes, automation, customer experience) which can be improved by AI implementation.
2. Define key problems in the business which can be solved by gen AI solutions and communicate these needs to their direct reports.?
3. Develop a plan to drive AI implementation in relevant areas across the business in order to solve the problems which have been identified.
4. Identify the necessary budgets and resources needed for AI implementation

Managers / Business Unit Leaders:

1. Initiate discussions with wider teams on AI and prioritize the uptake of AI tools across workflows in teams.
2. Support senior executive levels in recommending budgets, resources, platforms and vendors to support in the AI adoption process.
3. Communicate AI implementation plans to business units
4. Make decisions on the most appropriate AI tools / vendors as partners for the business
5. Rethink scope of work by: thinking critically about how to scale the impact of their own teams with AI

Emerging / Individual Contributors:

1. Contribute ideas to how gen AI can improve business performance and processes
2. Contribute knowledge on relevant gen AI tools and technologies for workflow processes
3. Able to apply AI chatbots / tools at work, such as using AI to automate processes or to replace administrative tasks
4. Rethink scope of work: think critically about current scope of work and how to integrate AI

Employee level:

The expectations for each employee level is differentiated due to the different roles and responsibilities across the business.

Business Impact??

Core Principle: We ask the question - how can I achieve maximum business and commercial value with generative AI in my business strategy?

Employees, depending on their level of seniority, will design strategy and implement action plans which lead to business value creation. The successful display of this competency will depend largely on AI mindsets towards adoption and transformation.

Display of Competency:

Senior Executives:?

1. Determine how gen AI impacts different business lines and overall shareholder value
2. Integrate and incorporate gen AI into both long-term and short-term business strategy?
3. Communicate business objectives, strategy and mission to key stakeholders such as shareholders, board members and employees
4. Determine AI transformation strategy for the organization and communicate strategy to direct reports.
5. Create clear communication channels from leadership to other parts of the business to support AI transformation mindsets

Managers / Business Unit Leaders:?

1. Translate gen AI strategy developed by top leadership into actionable steps which impact core business areas such customer experience and employee experience..
2. Translate gen AI strategy into consistent messaging across their teams and business units
3. Oversee execution of gen AI implementation
4. Carrying out upwards and downwards stakeholder management to ensure clarity of messaging across all levels and teams in the organization

Emerging / Individual Contributors

1. Actively support gen AI implementation and integration.
2. Participate in the change and transformation process through upskilling and job rescoping.
3. Support the uptake of new gen AI tools and processes.?
4. Adapt to new processes and new ways of working quickly.?

For a quick and visual summary of the competency framework, please refer to the graphic below.? I hope you find that carrying out an analysis of your company’s gen AI competency will be meaningful and useful in directing your own gen AI adoption strategy and practice as well.?

P.S. If you'd like a high-res version of this infographic, do ping me and I would be happy to share it with you.