What does it take to be an enterprise of the future?

IF WE had posed the question “What does the enterprise of the future resemble?” just a year ago, it is unlikely that many of us would have envisioned the current reality: a world where generative artificial intelligence (AI) is not only a pivotal element shaping the business insight generation but also an integral part of our everyday lives.

While the recent breakthroughs in AI have reinfused business transformation efforts, they have also renewed a strong appetite for policies and governance that regulate the ethical use of AI. In fact, the Singapore government has recently revised its national AI strategy to reflect the rapid development of the technology as it gains momentum and shifts from “good to have” to a necessity.

Evolving from the initial pattern recognition programs of the 1950s to today’s more accessible large language models, the presence of AI in the business sphere is not new and spans decades.

In fact, the latest research by Alteryx revealed that nearly eight in 10 say AI is already impacting what their organisations can achieve. Already transcending its hype status, this AI movement has become a rocket ship for significant technology changes – rapid transformations set to shape how future enterprises operate and perform.

But for many business leaders, this recent rapid and widespread adoption has taken even the most prepared by surprise – as they continue to navigate tight budgets while trying to prepare for this increasingly complex, data-driven future.

So, what can business leaders and IT decision-makers do to help their enterprises prepare for what lies ahead?

1. Understand 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. Increase 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. Incorporate 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. Foster 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 technology advancements, it is crucial that we practise empathy. Naturally, there is some fear that technologies like AI will replace human workers. So, 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.

Undoubtedly, data-driven decision-making will remain the lifeblood of tomorrow’s business, but only enabling the workforce to acquire the necessary data and analytic skills will drive true transformative change. The organisations that will thrive as enterprises of the future are those that have nurtured and equipped their domain experts with essential critical thinking, domain knowledge, data literacy, and analytical skills to navigate this era of AI-driven intelligence.

The writer is senior director of Asia at Alteryx