Assessing organizational readiness to embrace the AI revolution

Business leaders often find their relationship with technology-led disruptions to be both challenging and inspiring. The launch of Generative AI and its rapid adoption is one such disruption that empowers organizations to uncover valuable insights, make data-driven decisions, and automate repetitive tasks, leading to improved operational efficiency and overall performance. However, adopting AI also brings challenges related to organizational change, skill development and more.

The introduction of OpenAI, Google Bard and related ecosystem has completely changed the perception of business leaders. Today the majority have realized that AI has emerged as a powerful enabler, revolutionizing technology with its multitude of recognizable components. It has facilitated companies to develop or acquire seamless applications and platforms for a wide range of organizational functions. AI’s ability to analyze vast amounts of data, learn from it, and make informed decisions has made it an essential tool for businesses across industries.

The fundamental reasons for any organization to adopt AI in its functions can be summarized as:

Increasing efficiency and productivity:

AI improves efficiency and productivity by automating repetitive tasks, allowing human resources to focus on strategic and creative activities, leading to overall operational effectiveness.

Powering innovation and competitive edge:

AI serves as an enabler for accelerating product/go-to-market (GTM) roadmaps, enabling organizations to keep pace with changing industry and customer needs.

With the continuous evolution of AI, a wave of new job roles is emerging to oversee its development and management. These positions demand specialized skills and qualifications to ensure the ethical and responsible implementation of AI technologies. These professionals play a critical role in navigating the complexities of AI, ensuring its proper development, seamless integration, and ethical usage across various industries.

However, the usefulness of AI extends beyond purely technical staff, as it has the potential to transform work tasks across all types of occupations.

While AI development requires IT specialists to create the software, the number of these roles is relatively small compared to the broader range of roles that AI will impact.

This holistic approach ensures that the benefits and implications of AI are considered for a diverse range of stakeholders, facilitating effective adoption and utilization of AI technologies throughout an organization.

This AI adoption model can be visualized as a pyramid. At the top of the pyramid, we find the most talented and skilled AI experts. These experts innovate Large Language Models (LLMs) and lay the groundwork for the core software, enabling organizations to leverage AI technology effectively. Their expertise serves as the bedrock upon which the entire AI adoption journey is built.

These individuals typically have advanced qualifications, such as Ph.D. graduates or experienced AI developers employed by companies engaged in cutting-edge applications like ChatGPT or Google BARD. The number of people at the first two levels, including AI experts and related professionals, is relatively smaller compared to the larger number of users at the lower levels.

Moving down the pyramid, the subsequent levels encompass AI consultants and professionals who focus on various aspects such as technology adoption, integrations, business partnerships, and end-user engagement. These individuals build upon the research and development work conducted by the experts at the top two levels and transform the technical advancements into practical solutions, developing robust platforms or applications that incorporate refined AI models.

For instance, these professionals may include developers who specialize in building applications that leverage AI technologies like ChatGPT to automate creative writing jobs. The work of these professionals builds upon the foundational research and development conducted by experts at the higher levels of the pyramid, resulting in practical, real-world applications that bring AI benefits to a broader audience and various industries.

These end users interact with AI-powered applications and benefit from the insights and functionalities provided by the technology. Companies must proactively plan for this group to ensure a smooth transition and effective integration of AI-driven solutions into their work processes.

Selecting the right AI framework is a critical decision that can significantly impact the success and effectiveness of AI deployment in an organization. One crucial aspect to consider is whether to buy an existing AI framework or build a custom one. Companies focused on research and core software development would typically opt to build their own custom AI frameworks to establish their intellectual property (IP) in the market. This approach allows them to have full control over the development process and tailor the framework to their specific needs. Such companies will need people for the roles and skills that are at the top levels (levels 1 and 2) of the Mercer | Mettl AI adoption framework.

However, for most companies, AI adoption will revolve around two key areas: buying and utilizing existing AI models in product development and leveraging ready-to-use AI applications to enhance workforce productivity and efficiency. These companies, encompassing a significant portion of the workforce across various industry segments, would require AI enablement for roles in levels 3 and 4 as outlined in our AI adoption framework. In future blog posts, we will delve deeper into each level of this pyramid, exploring the roles in depth and understanding the key and peripheral skills organizations need to cultivate to thrive in the era of AI-led disruptions.

The AI revolution is well underway, and organizations must prepare themselves for its impact and embrace the opportunities it presents. To embark on a successful AI adoption journey, organizations should develop a structured approach and foster a culture of experimentation.

The Mercer | Mettl AI adoption framework serves as a guide for organizations to understand the different levels of expertise and skills required for successful AI implementation. By leveraging this framework and continuously building the necessary competencies, organizations can position themselves for success in the rapidly evolving landscape of AI.

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