By Souma Das, Managing Director, India Sub-continent at Alteryx
If we had envisioned what the enterprise of the future might look like just a year ago, it’s unlikely that many would have foreseen the current reality—a world where generative artificial intelligence (AI) is not only a crucial element shaping business insight generation but has also become an integral part of our everyday lives.
While AI presents unparalleled opportunities for businesses, it also entails significant responsibility. The direct influence it wields on people’s lives has prompted substantial inquiries into AI ethics, data governance, trust, and legality. According to a recent report by NITI Ayog, India’s national AI strategy should be tailored to its unique needs and aspirations based on a framework encompassing three interrelated components. It should focus on the economic impact of AI on India, viewing it as an opportunity for substantial economic growth. Additionally, the strategy should also prioritize AI for Greater Good, emphasizing social development and inclusive growth. Lastly, it should position India as the AI Garage for 40% of the world, aiming to be the solution provider of choice for emerging and developing economies globally.
Having evolved from the initial pattern recognition programs in the 1950s to the present-day more accessible Large Language Models, the presence of AI in the business realm spans decades. According to recent research by Alteryx, nearly eight in 10 (78%) of India business leaders acknowledge that AI is already influencing what their organizations can achieve. Beyond the initial hype, this AI movement has become a catalyst for significant technological changes, propelling rapid transformations that will shape the operational landscape of future enterprises. However, for numerous business leaders, the unexpectedly swift and widespread adoption of AI has caught even the most prepared off guard, as they grapple with navigating tight budgets while gearing up for an increasingly complex and data-driven future.
So, what can business leaders and IT decision-makers do to help their enterprises prepare for what lies ahead?
1. Understanding your data
The world is data-rich. In fact, IDC predicts that the collective sum of the world’s data will reach 175 zettabytes by 2025 – equivalent to streaming the entire Netflix catalogue millions of times over. But data is dirty and everywhere. The sheer amount of data would leave some companies struggling to convert it into meaningful decision intelligence.
In today’s fast-paced, data-rich business environment, the key difference between organisations that lead the pack or lag behind is the ability to sift through vast amounts of data, identify patterns, and extract meaningful insights without the bottleneck of manual processes.
Data in isolation alone will not provide the insights required for decision intelligence that delivers business value. Leveraging accessible, low-code, no-code advanced data analytics can empower all employees, including non-technical employees who do not know how to code, to unlock new insights and decision-making based on accurate data. Transcending traditional manual processes and harnessing advanced data analytics will set apart forward-thinking enterprises, enabling them to innovate, adapt, and lead.
2. Increasing collaboration between business and IT
Most organisations know what goals they want to achieve, such as generating more revenue, retaining customers, increasing the average deal size, and expanding to different markets. The hard part is figuring out what insights are needed to achieve those goals and if your data ecosystem will provide the data sets required to uncover the trends and patterns needed for more informed decision-making.
Some questions to help scope out your data ecosystem and if your analytic goals will deliver on business goals are:
• What data is needed to meet business objectives?
• Does the data even exist?
• Who needs access to or answers from the data?
• How can I collaborate with my IT teams to obtain some of these answers?
• How do you use the information to meet the business goals?
Together with the IT team, they can evaluate the data analytics tools and technologies needed to improve their data ecosystem, such as removing duplicates, handling missing values, and standardising data formats. With the insights uncovered, leaders can plan ahead, get the right teams involved and better inform employees with a roadmap to achieving those business goals.
3. Incorporating a modern and flexible governance framework
With countless data-driven AI technologies and intelligent systems available to accelerate speed to insight, it is crucial to account for data quality, security and governance guardrails required for accurate and intended outcomes.
A robust governance framework should be at the heart of these practices and ensure compliance with policies to effectively manage risks. It involves tailoring approaches to different processes and their associated risks, ensuring auditability, and adhering to security measures compliant with major standards.
This holistic approach to governance will allow for the safe scaling of data and analytics projects, with centralised control and oversight, ensuring end-to-end traceability and robust data security protocols.
4. Fostering a culture of change and empathy
Preparing for what lies ahead goes far beyond just implementing the right technologies, it is about developing a culture that embraces change with empathy. Cultivating a mindset across the organisation that values innovation, continuous learning, and agility ensures that every employee charges forward with confidence.
In times of economic uncertainties and technological advancements, it is crucial that we practice empathy. Naturally, there is some fear that technologies like AI will replace human workers. As such, leaders must help employees understand that technology is here to augment their roles and empower them to spend more time on other valuable tasks. The key to embracing any new technology and providing access at scale is to get everyone in the team on board.
Whether greeted with excitement or anxiety, leaders must champion this culture of change by encouraging employees to seek new ways of working while ensuring they remain engaged and valued.
Certainly, data-driven decision-making will undoubtedly continue to be the cornerstone of future business attempts. However, true transformative change will only be achieved by empowering the workforce with the essential data and analytic skills. Enterprises poised to thrive in the future are those that have cultivated and equipped their domain experts with crucial attributes such as critical thinking, domain knowledge, data literacy, and analytical skills to adeptly navigate the era of AI-driven intelligence