Nitin Rakesh is the CEO and Managing Director of Phase and co-author of the award-winning book “Transformation in Times of Crisis.”
As public intellectual and author Yuval Noah Harari said: “The secret of Sapiens’ success lies in flexible cooperation on a large scale. This made us the masters of the world.
In an interview with Smithsonian Review, Harari draws attention to some of the attributes that distinguish our species. One of the characteristics he highlights is our ability to rely on foreigners within the framework of vast cooperation agreements.
Although every business relies on this approach to operating, its ability to move forward is, in my opinion, the result of an opposing impulse. A solitary commitment to exclusivity and excellence to ensure a company stays above the competition.
In many ways, this is comparable to the trajectory the data has taken. Its journey over the past few decades has seen it go from being important to businesses to fundamental. At the same time, data science has become an exclusive niche field. Its practitioners typically operate separately from core business teams and provide key insights that can boost company operations.
However, as the need for more data-driven business insights grows, demand outstrips supply. There simply aren’t enough individuals and teams with the training and expertise required to meet companies’ exponential needs for data-driven expertise across all aspects of their business functions.
The promise of generative AI
In this context, the rise of artificial intelligence (AI), in particular generative AI (GenAI), constitutes an important and relevant development. With its distinct usability and ability to generate a variety of results in response to prompts, GenAI demonstrates the potential to democratize the rarefied field of data analytics.
Take, for example, its unparalleled ability to learn from massive amounts of data and create new content independently. GenAI not only facilitates text mining but also performs natural language processing (NLP) and data extraction from large and heavy files like PDFs. Advanced technology and deep learning algorithms help to open the doors to data, allowing everyone to take an interest in it and better understand it. This is a significant development.
Democratizing data science
Never before has analytics-based decision making been as crucial to business development as it is today. In an uncertain and unpredictable macroeconomic environment where the customer is in control, businesses cannot afford to wait for insights from the small group of existing data scientists. They need it to inform every decision in every action they take.
Conversely, even if the existing pool could magically expand, these specialists would not have the expertise necessary from having worked in other areas of a company to be able to provide specific information to a domain. Whether it’s the HR function, supply chain management or the finance department, only employees who have worked in these areas have the knowledge and expertise on what works and what is needed to move to the next level. This then comes down to giving each employee the access and expertise to become data scientists in their own fields.
Overcoming challenges and empowering the workforce
With its data analytics capability and availability through innovative platforms, GenAI can help equip everyone within an organization with the appropriate tools to derive crucial business insights from data. Technology along with big language models have the power to liberate predictive analytics from its current siled practice so that any employee can make data-driven decisions to advance business outcomes.
That said, it is equally important to remember that, like any other new technology, GenAI comes with its share of concerns and challenges. One of them concerns security. To ensure that GenAI is monitored and used safely, it is important that companies research and invest in tools and processes that can correct bias as it occurs. This will prevent these biases from coloring GenAI’s responses. Additionally, this can be achieved by partnering with specialists who can detect security threats in real time and implement automated responses to limit any potential damage.
Companies must properly prepare their employees to use this technology. Because new technologies are often intimidating, exploring preparation programs can help employees become familiar with new technologies in safe environments so they can use GenAI at work effectively and quickly.
Although business leaders are aware of the need to equip all of their staff with the tools and skills needed to improve their business results, they are hesitant to provide access to data. According to a survey conducted to assess the current state of decision-making in large multinational companies, while 80% of executives agree that the ability to analyze data has a positive impact on decision-making, 65% believe that employees with decision-making authorities should not have access to the data.
This disconnect will take time and knowledge to bridge. Concerns and apprehensions about the misuse of data and who can and should have access to it will need to be addressed. However, it is clear to me that advanced technologies such as generative AI can help be a game changer for businesses by enabling everyone, across all functions and domains, to harness the insights provided by predictive analytics.
The future will see much more human-machine collaboration, and it’s important to approach these innovations with security in mind as we learn to collaborate with technology. This way we can guarantee that it brings us results that can become revolutionary.
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