Alcinda Moezelaar, head of sales enablement at treasury and trade solutions, Rand Merchant Bank, believes generative artificial intelligence (GenAI) is poised to redefine data storytelling, but cautions that there is still a definite need for human skills.
According to Moezelaar, data storytelling has always been a component of business intelligence (BI), even if it wasn’t explicitly named as such.
“Traditionally, storytelling involved creating dashboards, exporting visuals to PowerPoint and presenting structured reports. However, true data storytelling goes beyond visualisation: it requires understanding the context of data, defining the audience, and crafting a narrative that makes sense to decision-makers,” she says.
"It’s not just about putting visuals together. It’s about understanding what real insights the data provides and tailoring the message accordingly. The way I present information to executives is very different from how I would communicate with data analysts."
Moezelaar sees GenAI as the ‘science’ of BI storytelling – a tool that supports the ‘art’ of storytelling. While AI can automate tasks such as segmenting audiences, generating visuals and even summarising insights, she maintains that the human element remains irreplaceable.
"GenAI can help with the technical aspects of storytelling by running through vast datasets, automating insights and personalising narratives. But it is humans who bring creativity, emotional intelligence and contextual reasoning to storytelling; qualities AI lacks,” she says.
Moezelaar also cautions about over-reliance on AI-generated outputs.
“Despite its benefits, GenAI comes with inherent risks. For example, AI-driven insights are only as reliable as the quality of the data fed into them. If the data is flawed or biased, GenAI will generate inaccurate insights," she says. "So, while it can be a valuable tool, there still needs to be human oversight to verify and corroborate AI-generated findings."
Another concern is misinformation. Large language models sometimes produce outputs that sound plausible, but are factually incorrect. “It is up to humans to use their own knowledge and experience to identify anomalies and inaccuracies, even in nuance, to ensure the accuracy of AI-generated insights,” she adds.
Into the future
Looking ahead, Moezelaar envisions a future where GenAI serves as a collaborative co-author in data storytelling. AI will handle the technical heavy lifting – processing data at scale, identifying patterns and creating visual representations – while humans will provide business acumen, empathy and contextual understanding.
"I see a strong collaboration between humans and AI," she says. "The future of GenAI in data storytelling will be a blend of art and science, rather than one replacing the other."
For businesses to fully capitalise on GenAI, Moezelaar says a strategic approach that includes piloting AI use cases before full-scale implementation is essential. She also emphasises the need for organisations to invest in training employees to use AI effectively.
"There’s still a lot of fear around AI replacing jobs," she notes. "But the focus should be on upskilling employees and encouraging them to embrace these tools. Leaders, in particular, need to lead by example in adopting AI-driven solutions.
"AI is here to stay, and it will disrupt how we work. If we are to harness its benefits, businesses need to proactively educate their workforce on how to use AI effectively."
Although the rise of GenAI is undeniably transforming how organisations handle data, Moezelaar is adamant that it should be viewed as an enhancement, rather than a replacement for human expertise.
“The key to success lies in understanding AI’s strengths and limitations, ensuring data quality and fostering a culture of continuous learning. GenAI doesn’t eliminate the need for human storytellers — it empowers them.
"By striking the right balance between AI’s efficiency and human creativity, we can unlock the full potential of data storytelling in the years to come."
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