How AI Builds Efficiency for Smarter Decision-Making Across Finance and Marketing

Artificial intelligence is now mainstream within enterprise automation, efficiently picking up tasks and building a level of agility within an organisation across functions from finance to marketing. Financialexpress.com, in association with Oracle, recently organised a roundtable of some of the brightest minds in marketing and finance from across sectors – top CFOs and CMOs in the room to gauge how AI is changing the way they approach business and how it helps in efficient decision-making.

From data to decisions: Harnessing AI for strategic finance leadership

At the roundtable of finance professionals, the shift in mood was palpable, from cautious optimism a couple of years ago to seeking efficient AI solutions for better decision-making. Participants were optimistic about AI’s potential and pragmatic about the challenges with its implementation and governance. The consensus was clear. The shift from the finance function being reactive to being predictive is inevitable, but it’s still a complex journey.

The fundamental challenge, repeatedly highlighted, is the state of the data itself. Professionals stressed the "garbage in, garbage out" principle, noting that integrating disparate legacy ERP systems into a unified data lake or unified database is a hurdle. They want simplification, standardisation, and automation.

Several participants highlighted that the immediate monetary benefits of these complex digital transformations are often difficult to immediately quantify. In fact, some pointed out that despite advanced tools, Microsoft Excel still dominates much of the finance function, underscoring the challenge of large-scale adoption and resistance to change within organisations.

Some of the CFOs highlighted the potential business value of AI in their organisations with concrete examples, such as predicting hospital occupancy and billing or enhancing scenario planning in FMCG. AI is seen as a tool to lower manual effort and provide faster insights. It has allowed CFOs to make a critical shift to be "available" and predictive rather than "busy" and reactive. In global contexts, AI can even serve as a bridge between the systems of developing and developed countries.

The debate got lively around AI’s key role. Is it a decision-maker or a scenario generator? Participants largely agreed that the human-in-the-loop is indispensable. While AI is excellent for generating scenarios, identifying trends, and predicting cash flow, the ultimate control and data validation must remain with human leadership. The goal, they concluded, is often to get a sense of trends and speed, not necessarily 100% initial accuracy, leaving the final accuracy monitoring to humans.

Participants raised concerns about governance. Training AI on public platform data presents a risk of biased models and limits utility where specific, proprietary data is lacking. To mitigate this, firms need to focus on building a persona and training AI on specific, desired data sets, ensuring the system can adapt to policy changes. Ultimately, for AI adoption to succeed, firms must look closely at the budget versus the benefit.

Unifying customer journeys: Powering personalisation with connected data and intelligent engagement

One of the leading themes that came out from the roundtable with some of the brightest marketing minds is how the transformation of unstructured data into structured data itself is proving to be truly transformative for organisations. Organisations sit on a goldmine of interactions—on social media, website content, customer service transcripts, and offline—and these have largely been fragmented pieces of information. Marketers create unified customer profiles by systematically organising this information, breaking down long-standing silos and gaining an unprecedented understanding that improves marketing effectiveness manifold.

For marketing leaders in today's dynamic digital landscape, cybersecurity has transcended from just a focal point to a foundational concern. As customer data continues to grow exponentially and digital touchpoints proliferate everywhere, the protection of information is no longer just a question of compliance but essential for establishing brand trust and loyalty.

But it's not just technology. Removing bias in data analysis and campaign execution is of equal importance. Any biased data or algorithms will result in skewed personalisation, alienate segments, and undermine business results. Leaders promote regular bias checks and diverse data teams so that personalisation is indeed inclusive.

The discussion also centred on the strategies of hyper-personalised engagement across digital, social, mobile, and in-person channels. Marketing leaders concurred that such an integrated approach, powered by advanced analytics and real-time insights, really empowers brands to connect with customers at meaningful moments.

Here, customer data fuels predictive marketing -- marketers can anticipate customer needs and build proactive campaigns toward better experience and conversion rates. Meanwhile, personalisation has to be balanced with data privacy and consent compliance. Transparency and ethical use of data were emphasised in devising experiences for each person, with marketers continuing to respect customer rights and the rapidly changing regulations on privacy.

Emerging technologies, most notably AI and machine learning, are making seamless omnichannel experiences possible. The tools empower real-time journey mapping, instant personalisation, and unified brand storytelling, regardless of where or how a customer interacts with a business.

To gauge success, marketing leaders are adopting nuanced KPIs that go beyond campaign reach or clicks to include deeper metrics: customer lifetime value, engagement rates, and brand advocacy. Participants foresee that, as AI and machine learning continue to evolve, there will be a major shift in how businesses nurture brand loyalty, create lasting customer engagement, and optimise marketing ROI-all via smarter, bias-free, and secure data practices.

Leaders also highlighted the need to continually upskill teams on emerging technologies, data analytics, and privacy laws, ensuring that organisations remain agile and competitive in a fast-changing marketplace. Ultimately, the transformation of marketing hinges not only on harnessing data but on fostering a culture that values innovation, ethical practices, and sustained customer trust.