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- 15 Apr 2024
Generative AI is rapidly expanding and influencing various functions across industries. In a recent presentation by Sequoia Capital, a graph highlighted the impressive growth of generative AI. What took SaaS 10 years to achieve in terms of revenue, generative AI accomplished in just its first year of deployment. As a result, companies are actively seeking talent capable of driving innovation in this field.
Talent, or the absence thereof, is increasingly becoming a focal point for organizations. Two weeks ago, Microsoft boldly hired over 70 top-tier AI engineers from Inflection AI. Their strategy? They invited them to a conference and presented an offer to be acquired that was too good to refuse. This strategy is often called acquihire in the industry. Only a few companies have the financial resources and vision to support such a daring move. As for the rest of us? We need to approach talent intelligence and recruitment with a scientific mindset. This is why I have emphasized the significance of these functions for quite some time.
In this skill-building journey, we must remember the Dunning-Kruger effect. The Dunning-Kruger effect essentially suggests that we often overestimate our knowledge, particularly in new domains. In other words, we sometimes lack the expertise necessary to identify what expertise we need to develop accurately. In HR terms, we may not have the skills required to define the skills we need to build for the future. This can lead to a gap between the skills we think we need and the required skills, potentially hindering our growth and innovation. It’s crucial to approach skill development with humility and a willingness to learn to ensure that we are effectively building the capabilities to drive our organization’s success.
This effect is quite prevalent in defining the roles and responsibilities. To demonstrate this, we looked at the recent job description of the role of Financial Analysts. We looked at the role of a Financial Analyst across two industries (posted within the last week). Both roles have more or less the same experience levels (one is 3 to 5 years, and the other is 4 to 5 years of experience). Here is the summary. (not showing the full job description, but focussed on the qualifications)
Qualifications highlighted in a Financial Analyst job description of an Industrial Company
- Proficient knowledge of MS Office, Word, PowerPoint, Access, and Excel.
- Knowledge and experience in working with Financial Reporting Software.
- Ability to work with minimal supervision or within a team environment.
- Ability to analyze problems and create solutions.
- Knowledge of financial theory and valuation.
- Ability to understand and solve complex financial transactions.
- Strong verbal and written communication skills.
Qualifications highlighted in a Financial Analyst job description of an Innovative Tech Company
- Power BI / Tableau or other data visualization experience preferred.
- SQL / R / Python or other programming/data science exposure preferred.
- Proven ability, experience, and overall understanding of fundamental finance and accounting acumen, including data modeling, data analytics, FP&A, forecasting, interpreting financial statements, and reporting.
- Capable of working with a high degree of ambiguity in a fast-paced environment.
- Demonstrated ability to work independently and collaboratively with multiple business partners and teams.
Based on my observations, the first job description shows signs of the Dunning-Kruger effect. This means it fails to recognize the job role’s evolving nature accurately. The rate of change in various job roles has accelerated significantly in recent times, and job descriptions must keep pace with these changes. We must thoroughly reevaluate all job descriptions to ensure that they accurately reflect the current technological and organizational change landscape. This is essential for attracting the right talent and aligning employee expectations with the realities of their roles in a modern, dynamic work environment.
It might be more effective to gain a competitive advantage by identifying and focusing on the emerging skills within each function. For example, let’s consider the evolving skill set in the realm of call center/customer service. (please see the chart below) While customer service will continue to rely on essential human elements in the future, AI-driven recommendations will also substantially increase. However, human intervention will remain crucial. The ability to empathize with customers, understand their needs, and provide personalized solutions will still be at the heart of effective customer service. As such, training programs and job descriptions in this area should reflect a blend of technical proficiency in AI tools and strong interpersonal skills to ensure a balance between efficiency and human connection. Understanding the digital transformation initiatives a company is undertaking across the functions will be helpful.
Summary: Organizations must strategically navigate talent acquisition and development to stay competitive in the dynamic AI landscape. Evolving Skill Requirements should be understood with the future in mind. It may be helpful to understand the digital transformation initiatives that the company is undertaking so that such skills can be reflected in the hiring requirements.