January 5, 2025
Managing Partner
Generative AI is set to transform 90% of technology jobs, prompting tech leaders to strategically mobilize talent and restructure their organizations to maximize AI's potential.
Santiago & Company predicts that generative AI (GenAI) will profoundly impact 95% of technology jobs. This transformation presents technology leaders with significant challenges in an already intricate market for tech talent. They must navigate the dual responsibility of enhancing GenAI capabilities within their departments while spearheading its implementation throughout their organizations.
To thrive in the evolving tech landscape, leaders must reconsider their approach to talent mobilization in response to the rise of generative AI (GenAI). Santiago & Company estimates that AI will either reduce costs or free up approximately 10-15% of capacity in the tech function, allowing leaders to reallocate resources to other critical areas. GenAI is poised to provide the most significant economic uplift and change to work since the agricultural and industrial revolutions, leading to a reinvention of work with more human-centric work processes.
The rise of GenAI necessitates a shift in roles and skills for most tech positions as it becomes an integral part of processes and workflows. GenAI will streamline many tasks within tech functions, increasingly automating code generation for app development and transactional processes in tech support, reducing the resources and time required for these tasks.
AI and GenAI are creating new roles, such as the Chief AI Officer and a senior executive overseeing all AI initiatives, including predictive AI and GenAI projects. Organizations will also need prompt engineers to craft and refine inputs for GenAI solutions. LLM operations engineers will also be needed to simplify and automate prompt processes and fine-tune models.
As GenAI becomes more prevalent, skills will adapt accordingly. The evolution is evident in roles such as data scientists, who must handle larger volumes of unstructured data to train large language models (LLMs) and, derive insights, and upskill in prompt engineering and AI model fine-tuning. Over time, proficiency in GenAI will become essential across various tech and digital roles. Technology leaders must meticulously design their organizational structures to harness the transformative potential of Generative AI. This involves strategically positioning GenAI's capabilities and expertise to maximize their impact. In the public sector, where GenAI promises substantial enhancements, governmental bodies at all levels—national, state, provincial, and local—must proactively embrace these opportunities.
Establishing a GenAI center of excellence is a critical step for organizations aiming to harness the transformative potential of generative AI. This centralized hub consolidates GenAI expertise within the tech division, ensuring a focused and strategic approach to adoption. By centralizing resources, organizations can accelerate the deployment of GenAI across business functions while maintaining strict oversight of ethical and responsible AI usage. The center is a guiding body that establishes governance frameworks to address potential biases, data security, and privacy concerns. Cross-functional ambassadors, embedded within various business units, foster collaboration, ensure alignment with organizational goals and assist in training broader teams on effective GenAI utilization.
The benefits of this approach are manifold: it streamlines GenAI implementation, reduces redundancy, fosters innovation, and builds institutional expertise, enabling the organization to remain agile and competitive in an AI-driven landscape. By instituting a GenAI center of excellence, organizations position themselves to maximize GenAI's potential while mitigating associated risks.
GenAI is already transforming repetitive, rule-based tasks, pushing entry-level roles toward more strategic responsibilities. For example, customer support roles are evolving as basic troubleshooting and FAQ handling are increasingly managed by AI-powered chatbots. This shift requires customer support representatives to develop empathy and more advanced technical skills to handle complex issues. Over time, decentralizing this expertise becomes beneficial. As GenAI capabilities expand, organizations can transition to embedding GenAI squads within individual business units and support functions. These squads are tasked with implementing specific GenAI applications. At this juncture, the tech division's role evolves to focus on monitoring, governance, and continuously refining security standards and ethical guidelines.
While GenAI offers numerous benefits, there are also challenges to consider:
Simultaneously, technology leaders must reconsider their talent strategies in light of GenAI's increased capacity. They face two primary options. The first option is to reduce the headcount. As GenAI automates various processes, some organizations might cut specific roles, reallocating the financial savings to other areas. Many tech functions have traditionally concentrated on recruiting entry-level engineers via university partnerships and internship programs. However, with GenAI's rise, the immediate need for junior engineers diminishes. Consequently, tech leaders must focus on attracting more seasoned engineers until GenAI-related skills become a standard expectation for new entrants.
Furthermore, the career paths and performance management systems must adapt to accommodate the select top-tier employees skilled in designing and implementing GenAI solutions. These individuals will be highly sought after, necessitating strategic retention efforts. The employee value proposition remains critical in drawing and keeping senior talent with GenAI expertise. This approach ultimately results in a leaner tech function.
Alternatively, some companies might redeploy the talent liberated by GenAI advancements, channeling these employees toward other organizational needs. Positions like tech support, often based offshore, could be transformed into high-value, strategic roles. For instance, an offshore tech-support site could be repurposed into an innovation hub focused on a particular product or service. This shift requires comprehensive upskilling and reskilling initiatives. Effective capacity planning, both short and long-term, is vital to successfully redeploy talent across priority areas and address any talent gaps. Tech leaders must prioritize GenAI applications, identifying the capabilities required and determining where current tech talent can be most effectively redeployed, ultimately enhancing the tech function's value to the company.
In the face of an already competitive talent market, the demand for top tech talent will only intensify with the advent of GenAI. To navigate this landscape successfully, technology leaders should focus on key priorities. First, the organization must be rapidly assessed to gauge existing capabilities and identify where GenAI can make the most significant impact. Establishing a GenAI center of excellence within the tech division is crucial. Initially, prioritize a select number of use cases within the tech function and across a few business units to build institutional expertise and engage employees. As GenAI adoption progresses, governance structures must be constructed and refined continually, ensuring that the organization remains agile and effective in leveraging GenAI's potential.
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