Data: The Unsung Hero of the GenAI Revolution

By: Philip Madgwick, Regional Vice President of Alteryx Asia & ANZ

Beyond just empowering businesses to enhance productivity, generative AI (genAI) is unlocking new opportunities and driving growth across industries. However, not everyone is using genAI to its full potential and a lack of comprehension surrounding the technology has created a gap for onboarding the technology successfully. To fully reap the rewards, organisations must prioritise data as a strategic asset. High-quality data fuels genAI models, providing businesses with the essential foundation for generating innovative and accurate outputs. Simply put, the effectiveness of genAI applications is directly tied to the quality and quantity of the data they are trained on.

Data: AI’s Lifeblood

Data has become paramount to the success of various workstreams, to no one’s surprise. Its usefulness, however, is time-sensitive. According to an IDC study, up to 75% of data loses value within days if it is not constantly handled and renewed. Companies run the risk of having their AI initiatives become less effective if they neglect addressing data quality or accessibility through regular sanity checks.

Furthermore, a startling 70% of businesses acknowledge they are underutilising their data. This underutilisation prevents organisations from reaping the maximum benefits of genAI technology, often the result of creating departmental silos that restrict the free flow of information necessary for thorough training and efficient genAI model development. Scalability of genAI programmes is also hindered when data is not updated in a timely manner, rendering outputs generated by such technology outdated and irrelevant.

To optimise genAI usage, businesses also need to deal with the possibility of “AI hallucinations” through strong data governance procedures, which include safeguards for privacy, bias detection and data security. In a survey done by Alteryx surveying 2000 employees across 11 countries on business leaders attitudes towards genAI,  69% of business leaders in Singapore believe “AI hallucinations” negatively impact their trust in AI. Data governance becomes crucial in ensuring AI technology adheres to compliance measures by sourcing data ethically and accurately. This helps the public build greater trust in genAI to improve its uptake across industries.

Collaboration between humans and AI

In the same survey, 66% of business leaders report that their own job responsibilities have changed since the advent of genAI along with 67% of their team’s responsibilities. This technology’s impact is already being profoundly felt and can be expected to grow with greater advancements and human input. In today’s dynamic, digital landscape, where teams are under constant pressure to produce value-added results, low-code and hyper-automated technologies have been growing in popularity. According to a Gartner’s estimations, by 2024, companies anticipate a 30% decrease in operating costs by combining hyper-automation technologies with redesigned operational protocols. Through increased automation and data-literacy across functions, these tools can help close the gap between businesses and IT innovation to accelerate time to market for the organisation as a whole. These improved turnaround times then translate into higher potential for organisational profitability and productivity.

It is no wonder then, that genAI is now regarded as a key instrument in many workspaces. Adoption of this technology across various internal departments from business intelligence to customer support, marks a significant shift in this digitalisation era. GenAI has rapidly emerged as an indispensable tool across industries and a significant portion of today’s workforce already uses genAI in their daily functions.

Tailoring the right data-driven strategy

Greater acceptance and usage of genAI, however, may not guarantee business success. GenAI’s effectiveness is dependent on several factors including data quality, model complexity and specificity of the use cases to be addressed. If the data is biased, incomplete or of low quality, it can lead to inaccurate responses. The coordination and execution of an organisation’s various operations might be heavily reliant on processed and structured data ready for genAI’s analysis and recontextualisation. Especially in today’s data-driven world, where information forms the lifeblood of organisations, it is important to remember that humans are ultimately the foundational architects of these technologies.

Organisations must foster a collaborative environment where humans and machines can work together seamlessly to achieve business goals. For example, genAI can help provide accuracy, scale and speed while we, as humans, contribute contextual and directional cues, along with strategic thinking. The integration of both of these sets of strengths will enable businesses to optimise their resources. By integrating genAI into their internal workstreams, not only as part of their teams’ toolkits, but also as part of their upskilling programmes, organisations will cultivate a culture of innovation within the workplace.

This human-machine partnership, along with a robust, well-defined data management system, will help ensure success with genAI initiatives. By establishing clear objectives, data ownership, quality standards and accessibility, business leaders will enable their teams to actively prepare data for effective data blending, cleansing and profiling. This provides a solid foundation for impactful, actionable insights for business growth and workforce improvements. Given the rate at which AI is evolving, enabling familiarity with the technology will benefit businesses in the long run.

Fundamentally, organisations must prioritise data management as a cornerstone for their AI-driven initiatives. AI models are constantly learning and require the right contextual data to be trained on to deliver the best results for any business. By aligning data strategies with broader business objectives and leveraging AI capabilities to their fullest potential, organisations can better drive growth, improve efficiency, and gain a competitive edge in their respective industries.