In 2024, 77% of businesses are working with digitised data, underscoring its central role in decision-making. generative AI (GenAI) is emerging as a game-changer, helping businesses not just interpret but act on data swiftly and effectively, setting leaders apart from the competition.
The role of GenAI in reshaping how we interpret and leverage information cannot be overstated, and it is truly proving to be a differentiator, further separating early adopters and laggards. Traditionally, data has been siloed within specialist teams—scientists, engineers, and analysts—leading to bottlenecks that stifle agility and slow decision-making. By implementing GenAI products, businesses can break down these silos by enabling users at all levels to engage directly with data, putting data insights in the hands of every business user, engineer and application builder. When leveraging GenAI for data analytics, businesses are able to guide and automate certain tasks, cutting down the time this would normally take between different data teams, which in turn empowers users to be more productive and help employees serve themselves more efficiently.
Early adopters of GenAI for data analytics, like EcoLab and Verizon, are reaping significant rewards. EcoLab, a global sustainability provider, has trained GenAI on clients’ operational and financial data to quickly and effectively identify the best resources for them, reducing the cost of time and resources. This proves that companies who have already adopted the technology across their operations are seeing benefits such as democratised data access, the ability to deliver actionable insights rapidly and monitor the benefits which have the ability to transform the company. Through being able to leverage, analyse and make data-driven decisions quicker and more effectively through GenAI, employees can prioritise other operations, which accelerates a company’s growth and enables them to scale quicker.
As well as reporting operational benefits, companies are seeing a measurable return on investment with GenAI, reaffirming the technology as both a financial asset and a key competitive differentiator. For example, Verizon—the telecoms giant—has developed a “centre of excellence” which allows them to monitor the ROI they are receiving for GenAI, meaning they can constantly monitor the financial benefits they’re receiving from the technology, and where it’s proving to be most beneficial. When investments are made, it is important to show the value and return making it suitable for the bottom line.
Democratised data access for decision making across levels of a business enables businesses to grow, scale and become more efficient. This was highlighted in a recent report by MIT sponsored by ThoughtSpot found that nearly half of adopters of GenAI for analytics anticipate a 100% or greater ROI within three years. By moving away from a centralised framework, businesses enhance accessibility to data, and improve performance of data-driven decisions, which is beneficial for businesses in the long-run.
It’s a fact that innovation and originality is also crucial to empower and drive businesses towards efficiency and growth. GenAI for data analytics plays an important role in business innovation as through extracting insights from multiple datasets, GenAI can build a complete and personalise of different customers’ behaviour and habits in an instant. When using traditional in-house teams, although they may be able to reach the same conclusion, they may struggle to do it as quickly. Whereas harnessing GenAI for data analytics means results are achieved quicker, and therefore more can be achieved each day.
In the same way that GenAI has been widely adopted across businesses, agentic AI is now rapidly making inroads into businesses, and already transforming everyday operations. Agentic AI is offering businesses a step beyond GenAI—through operating autonomously to perform tasks in a human-like way. Agentic AI uses large language models (LLMs) to manage multiple agents, which can handle a vast range of operations from data search and analysis to driving complex data-led decisions. The technology’s systems go beyond when it comes to automating end-to-end processes, reducing manual effort and increasing efficiency across operations, to the point where they are widely described as being human-like.
Just as companies have been integrating GenAI products, more companies are now beginning to integrate agentic AI products into their ecosystems. Autonomous agents, such as Spotter, are allowing businesses to work with data in ways that hadn’t been previously possible – allowing them to converse with the system in the same way they would a human data analyst. By embedding the products into their existing business applications, when users ask questions of their data, they can now get the structured and efficient answers they need, which are adapted to both the industry and persona of its users.
To unlock transformative business value, companies must integrate GenAI and agentic AI without delay. Staying ahead of the curve ensures they dismantle bottlenecks, achieve rapid, data-driven insights, and enjoy substantial ROI—essential advantages in an AI-powered future.
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