Samuel Thompson

Coca-Cola is shifting its marketing strategy from price hikes to AI-driven persuasion to cultivate consumer demand. The company is integrating generative AI for creative development, optimizing campaigns, and streamlining content creation across digital platforms. This evolution moves AI beyond efficiency to fundamentally influence brand engagement and sales, signaling a broader industry trend towards automated marketing pipelines and data-informed strategies.

AI is transforming enterprise treasury management, moving businesses from error-prone spreadsheets to automated data pipelines. Experts highlight the need for digitized, real-time data as a foundation for AI implementation. Integrating treasury management systems with ERP platforms and trading systems is crucial for accurate insights, enabling better liquidity management, risk mitigation, and compliance. This modernization is essential for navigating market volatility and building financial resilience.

DBS Bank and Visa are piloting “Visa Intelligent Commerce,” enabling AI agents to initiate and complete purchases on behalf of customers. This “agent-driven commerce” shifts transactions from human to AI execution, with banks retaining control through tokenization and approval workflows. The pilot focuses on routine purchases, aiming to integrate AI more deeply into financial operations while addressing security and trust concerns.

Financial sector leaders are moving beyond AI experimentation to focus on operational integration for 2026. The shift is towards system-wide AI agents that manage processes within strict governance, requiring architectural and cultural adjustments. Key challenges involve coordinating legacy systems, compliance, and data silos to enable “agents” that run processes, not just assist. This necessitates a “Moments Engine” for signals, decisions, messaging, routing, and action, with governance as a foundational, hard-coded feature. Data architecture must enable restraint in personalization, and generative search optimization is crucial for off-site brand visibility. Agility will be achieved through structured, secure experimentation, paving the way for agent-to-agent interactions.

Integrating AI is a strategic organizational shift, not just a tech upgrade. A six-area framework guides planning and assessment, emphasizing data preparation as foundational. Success requires redesigning workflows, managing legacy systems with AI’s help, and converging physical and digital operations. Robust governance, including risk assessment and security, is vital. Sustainable AI success depends on leadership alignment, investment, and a realistic view of capabilities, addressing all aspects holistically.

SS&C Blue Prism is guiding clients from RPA to agentic AI, a necessary evolution for complex workflows. Traditional RPA struggled with unstructured data, while agentic AI, leveraging LLMs, can reason and adapt in real-time. SS&C Blue Prism focuses on an outcome-oriented approach, setting goals rather than dictating steps. While fully autonomous AI is still developing due to trust and regulatory concerns, SS&C Blue Prism is introducing new technology to embed AI agents into existing workflows, aiming to unlock significant further automation potential.

NatWest Group is significantly expanding AI adoption across customer service, wealth management, and software development, aiming for 2025 to be a key year for scaled deployment. Generative AI is enhancing customer interactions through the digital assistant “Cora,” and empowering staff with tools like Microsoft Copilot. The bank is also streamlining wealth management document processing and leveraging AI in software development, with AI contributing over a third of its code. These advancements are supported by infrastructure upgrades and a focus on ethical AI implementation.

Urban Outfitters Inc. is piloting agentic AI to automate weekly performance reporting, transforming a manual task into a software-driven process. This initiative allows AI systems to analyze store-level data and generate consolidated reports, highlighting key patterns and areas for attention. The goal is to reduce time spent on data collection, accelerate decision-making, and free up merchandising teams for strategic thinking. This move signifies a broader trend of autonomous AI integration into enterprise workflows.

University of Hertfordshire researchers have developed an AI forecasting model for the NHS, leveraging historical data and machine learning to predict healthcare demand. This system analyzes patient trends, workforce availability, and demographics to improve resource allocation, staffing, and patient care strategies. Focusing on system-wide operations, the model aims to shift healthcare management from reactive to proactive, enhancing efficiency and informing crucial strategic decisions. The project is ongoing and expanding its pilot testing to various healthcare settings.

Finance leaders are increasingly adopting agentic AI for accounts payable automation, driving an 80% ROI compared to general AI’s 67%. These autonomous systems handle complex tasks with minimal human input, necessitating a re-evaluation of automation budgets. While generative AI summarizes, agentic AI executes workflows, offering tangible business returns. Accounts payable serves as a key proving ground due to its structured nature. Organizations are deciding whether to buy or build AI solutions based on whether the function is a common process or a unique differentiator. Robust governance frameworks are crucial for safe and effective deployment, treating AI agents like junior colleagues with human oversight. Ultimately, purposeful implementation, not just experimentation, is key to realizing transformative results.