Using data and AI to drive career growth

This article has been originally published in Spark Magazine and others.

Artificial intelligence (AI) is no longer just a futuristic concept; it has become an integral part of our daily conversations, workplaces, and strategic decisions. From the boardroom to the classroom, AI is increasingly being seen as the key to future success. Its potential to transform both our professional and personal lives is undeniable. As the scope of AI applications grows, so too does the urgency to adopt it effectively. Many organizations and individuals, driven by a fear of being left behind, are rushing to implement AI solutions. Yet, in their haste, they often miss the crucial first step: understanding how AI works and, more importantly, how to lay the necessary groundwork for its success.

Despite the progress AI has made, its adoption is still developing. AI may be advancing quickly, but its full potential has yet to be realized. While early AI systems, such as IBM's Deep Blue, demonstrated its power, today's AI is moving toward a more transformative future—one that will be defined by artificial general intelligence. According to PwC's 27th Annual Global CEO Survey, 70% of CEOs expect Generative AI to significantly change their business within the next three years.

The landscape is changing every day, but one thread remains constant: data is the backbone of AI. AI systems need clean, well-organized, and accessible data to function optimally. But, in their eagerness to adopt AI, many organizations overlook the importance of establishing a solid data foundation. This oversight can not only lead to inefficiencies but also outputs that are inaccurate or even harmful. In fact, the risks of deploying AI without proper data management extend far beyond simply being "left behind"—they can damage decision-making processes and erode trust in AI-generated results.

As AI continues to reshape industries, understanding how to manage and leverage data is essential. This article delves into the importance of building strong data foundations to unlock the full potential of AI.

Data-driven decision making: A new imperative

The phrase "data-driven decision making" has evolved from being a buzzword to becoming a fundamental practice in today's business environment. It is now a key component of organizational success, e.g. in learning and development (L&D) and change management. However, while data-centric approaches are increasingly adopted at the leadership level, there is often a gap in how these strategies are applied throughout the organization.

For AI to be effective in learning and talent development, it requires a steady flow of accurate, relevant data.

For AI to be effective in L&D, it requires a steady flow of accurate, relevant data. Managers, L&D professionals, and change agents must embrace data-driven cultures, where decisions are not based on intuition but on concrete evidence. This shift is crucial, as data informs decisions about employee development, identifies skills gaps, and guides organizational change initiatives. However, fostering such a culture requires more than just gathering data. It involves a fundamental change in how organizations perceive and utilize information. Data must become an integral part of the decision-making process, and AI initiatives should be viewed as core components of strategic workforce development, rather than just technological add-ons.

Implementing a data-driven culture requires overcoming resistance to change and ensuring leaders at all levels buy into its value.

Implementing a data-driven culture is not without its challenges. It requires overcoming resistance to change, investing in scalable technology infrastructure, and ensuring that leaders at all levels buy into the value of data-driven practices. Moreover, organizations need to establish robust systems for data collection and analysis while simultaneously upskilling their workforce to interpret and act on the insights generated from data. This dual focus on technology and human capability is what sets successful AI implementations apart from those that fail to deliver results.

AI for personalized career growth: Empowered by data

One of the most exciting prospects of AI is its potential to personalize career development. PwC's recent report on Generative AI highlights how AI is currently being used to capture "low-hanging fruit" focusing on efficiency gains. While this is important, AI's true potential lies in its ability to go beyond simply speeding up processes. It can create individualized career growth opportunities tailored to an employee's unique skills, performance, and goals.

Today’s workforce demands a more customized approach to professional development, and AI, powered by data, is the key to making this possible.

Gone are the days when one-size-fits-all training programs and generic career paths were sufficient. Today's workforce demands a more customized approach to professional development, and AI, powered by data, is the key to making this possible. By analyzing comprehensive data on an employee's performance, skills, and aspirations, AI can generate personalized learning paths that adapt as the individual progresses. This ensures that development plans are dynamic and responsive, offering the most relevant opportunities for growth at every stage of an employee's career.

By analyzing comprehensive data on an employee's performance, skills, and aspirations, AI can generate personalized learning paths that adapt as the individual progresses.

 For professionals aiming to grow in an Al-driven world, understanding the role of data in this process is essential. Al may suggest learning opportunities, but these recommendations are only as good as the data they are based on. By engaging with data collection efforts and actively seeking out experiences that enrich their data profiles, professionals can enhance Al's ability to guide their career growth. Those who take an active role in managing their data can better leverage Al to shape their future careers. 
 

Upskilling in the AI era: Data literacy is the key

As Al continues to permeate every aspect of business operations, data literacy is becoming a critical skill for both organizations and individuals. To fully capitalize on the power of Al, organizations must ensure that their workforce is equipped with the knowledge and skills to understand and work with data effectively.

Data literacy goes beyond the ability to read charts or analyze spreadsheets. It encompasses a deep understanding of how data informs decision-making, the potential biases that can arise from flawed data, and the limitations of data in certain contexts. In the world of Al, data literacy is even more critical. It is the difference between blindly accepting Al-generated outputs and being able to critically engage with the technology to drive meaningful outcomes. It is also about see the customers and operations behind the data points rather than just seeing the numbers like an outsider.

Leaders in L&D and change management must prioritize upskilling their teams in the fundamentals of data analysis and interpretation. This does not mean turning every employee into a data scientist, but it does require creating a workforce that can ask the right questions, understand data quality challenges, run some quick analysis themselves, and interpret Al-generated insights within the context of their specific roles.

Professionals who aim to grow their careers in the Al by all employees. A data-driven culture helps ensure era must also recognize the importance of data liter- that Al initiatives are embraced and integrated into acy. While Al is a powerful tool, it is the understanding everyday business practices. of data that allows Al to function effectively. By developing strong data skills, professionals can position themselves as active participants in the Al revolution, rather than passive observers. They can contribute to data collection efforts, identify valuable data sources, and provide critical context that enhances Al's perfor-mance. In doing so, they become indispensable in an By focusing on these basics, organizations can avoid common pitfalls associated with Al implementation, such as overreliance on technology without proper data foundations. Ensuring that Al solutions are built on solid data allows businesses to maximize the benefits of Al while minimizing risks. Al-driven world.

Simplifying AI implementation: Back to basics

In the rush to implement Al solutions, many organizations overlook the foundational elements necessary for success. Before deploying Al, organizations must ensure that their data is clean, structured, and acces-sible. Al's potential can only be fully realized when the underlying data is well-organized and of high quality. 

 This back-to-basics approach involves several key steps:

1. Data Audit: Organizations need to assess the data they have, its quality, how it is stored, and who has access to it. Understanding the data landscape is the first step to ensuring AI success.

2. Data Governance: Establishing clear policies and procedures for data management is critical. Data governance ensures that data is handled consistently and responsibly across the organization.

3. Data Infrastructure: Investing in the right tools and platforms to collect, store, and process data efficiently is essential. A strong infrastructure supports the effective use of AI by ensuring data is available and ready for analysis.

4. Data Culture: Organizations must foster a culture where data is valued, and its importance is understood.

Career growth in the AI age: Data as the foundation

For professionals looking to advance their careers in the Al age, data proficiency is a non-negotiable skill. It is no longer enough to simply use Al tools. To truly thrive in this new landscape, professionals must understand how to harness data to generate insights and drive intelligent decision-making.

Data skills will soon be as essential as communication or problem-solving abilities. Professionals who can bridge the gap between Al capabilities and business needs will be in high demand. They will be the ones who can translate business challenges into data-driven questions, collaborate effectively with data science teams, and drive strategic use of Al within their orga-nizations. World Economic Forum's Future of Jobs Report projects that most of the jobs of tomorrow will be performed by using Data and Al.

As Al systems become more prevalent, data literacy will become a core competency for leadership roles. Future leaders will need to make decisions in environments where Al-generated insights are central to business strategy. Those who can critically evaluate these insights, understanding both their potential and their limitations, will be best positioned to lead their organizations in the Al-driven future.

While data proficiency is essential, it is also a journey. where data is valued, and its importance is understood Al and data science are complex and ever-evolving 
fields. Staying current requires a commitment to themselves for success in an Al-powered world. As Al lifelong learning. However, those who invest in devel-oping their data skills will be well-prepared to navigate the challenges and opportunities of the Al era.
 

Conclusion: The road ahead

Al is transforming industries at an unprecedented rate. However, to unlock its full potential, organizations and professionals must first build a strong foundation in data. Data is the fuel that powers Al, and without clean, well-organized, and accessible data, Al cannot deliver on its promises.

By embracing data-driven decision-making, personal- izing career development through Al, and prioritizing data literacy, organizations and individuals can position
themselves for success in an Al-powered world. As Al continues to evolve, the ability to work with data will become not just a technical skill, but a critical driver of career growth and organizational performance.

In this new paradigm, understanding data is the key for professionals to drive innovation in an Al-driven future and unlock the future of work.
 

About the author

Semih Kumluk, PhD is an award-winning Al thought leader with 15+ years in digital transformation, strategy execution, and innovation leadership.