A transformative shift is occurring in businesses as Chief Information Officers (CIOs) evolve into strategic architects. Our Global Tech Agenda 2026 reveals that proactive CIOs are integrating AI and data into their operating models, thus moving from simple technology management to actively shaping their companies' futures. This shift is evident in our research, which highlights a divide between those CIOs modernizing technology merely for efficiency and those leveraging it for competitive advantage.

Top-performing companies have begun to view technology as a value creator rather than a cost center. For example, forward-thinking CIOs are embracing agentic automation to redefine operational processes and data productization for generating new revenue streams. These initiatives lead to higher earnings before interest, taxes, depreciation, and amortization (EBITDA) growth. Collaboration between technology and business leaders is key; nearly half of high-performing organizations report ongoing strategic co-creation.

Companies like DBS Bank and Aviva illustrate the concrete benefits of AI integration. DBS Bank restructured its operations into over 30 customer-focused platforms, which led to enhanced innovation and coordination. Aviva, through deploying over 80 AI models in its claims process, significantly improved efficiency, reducing liability-assessment time by 23 days while increasing customer satisfaction scores.

While challenges persist—such as data foundation limitations and change management issues—leading companies are adapting by investing in talent and reskilling their teams. Top performers prioritize AI as a key investment area, with a significant proportion planning increased budgets. This focus not only drives innovation but also reflects a commitment to integrating technology deeply into their business strategies, ensuring that technology serves as a catalyst for sustained growth.

Brazilian carrier Azul Airlines has integrated artificial intelligence (AI) into its revenue management, network planning, and maintenance systems, which has led to substantial financial benefits, generating approximately $6 million in weekly gains. According to André Américo, the director of network and strategic planning and revenue management at Azul, AI has significantly enhanced the airline's operational efficiency.

In revenue management, AI algorithms analyze large data sets to optimize pricing strategies, ensuring that ticket prices are adjusted in real-time based on demand and competition. This proactive approach allows Azul to maximize its revenue potential for each flight.

In terms of network planning, AI helps in forecasting demand for routes more accurately. By analyzing historical travel patterns, seasonal trends, and customer preferences, the airline can strategically select routes to operate, reducing operational costs and increasing profitability.

Furthermore, AI plays a vital role in maintenance systems, predicting potential aircraft issues before they occur by analyzing performance data. This proactive maintenance strategy minimizes downtime, improves aircraft availability, and enhances safety standards.

Overall, the implementation of AI at Azul Airlines has not only improved financial outcomes but also streamlined operations, leading to better resource management and enhanced customer satisfaction. The successful application of AI in these areas highlights its potential to transform the airline industry, driving both operational efficiency and profitability.

The Strategic Imperative for CFOs to be AI Entrepreneurs
By Kelley Lynn Kassa, Senior Analyst, Data & Analytics at BARC

CFOs are uniquely positioned to transform data into actionable enterprise intelligence, especially as agentic AI and predictive planning revolutionize performance management. This shift places finance leaders in a prime position to bolster their organization’s data foundation and drive strategies that enhance value.

Agentic AI can fundamentally change corporate planning, forecasting, and performance measurement. According to BARC’s report, “Predictive Planning and Forecasting on the Rise – Hype or Reality?,” predictive algorithms have increasingly automated planning processes and improved forecasting accuracy. This ability to deliver quicker insights and facilitate deeper analysis can significantly enhance decision-making capabilities.

However, successful implementation of agentic AI relies on having a robust data foundation. CFOs must prioritize data quality, governance, and accountability, acting as key facilitators of AI integration into performance management. A BARC study reveals that 34% of organizations struggle with data architecture, highlighting the importance of clean and contextualized data for effective AI utilization.

As companies adopt advanced planning tools, the CFO’s role is evolving. No longer confined to traditional budgeting and reporting tasks, today’s CFOs are becoming proactive leaders who contribute to strategic decision-making across the organization. Research shows that 27% of organizations already use predictive planning, with 65% expecting significant benefits, including improved accuracy and reduced effort in FP&A activities.

To optimize AI's benefits, finance teams must integrate data from various sources, establish governance frameworks, promote data literacy, and collaborate with IT leaders. The future CFO will not only manage financial outcomes but also ensure that every decision is supported by trusted data, paving the way for enhanced corporate performance management.

HR’s Transformative Role in an Agentic Future

As agentic AI reshapes the workforce, HR leaders have a pivotal opportunity to redefine their function. This shift isn't just a technological upgrade; it demands a fundamental rethinking of HR’s role in organization dynamics. Agentic AI facilitates hybrid teams that encompass both human and digital labor, enhancing collaboration and necessitating a reconsideration of the entire talent framework. HR can steer this transformation, ensuring human experiences are prioritized while seamlessly integrating AI into workforce strategies.

Concrete Applications and Benefits:

1. Strategic Workforce Planning: Agentic AI enables dynamic, activity-based workforce planning that specifies task assignments among humans and AI. Real-time analytics allow HR to proactively forecast workforce needs and redeploy talent, creating a more agile organization.

2. Organizational Design: Future structures will emphasize outcomes rather than rigid hierarchies. Agentic AI supports scenario modeling and workforce insights, empowering HR to collaborate with leadership in crafting innovative operating models.

3. People Attraction: HR should focus on meta-skills such as adaptability and capability for human-agent collaboration. Enhanced technology in sourcing and screening streamlines the recruitment process, improving experiences for all parties involved.

4. Hybrid Learning and Development: Continuous learning will merge with work, utilizing AI for personalized upskilling. This ensures that workforce capabilities evolve in line with motivational changes in technology and enhances collaboration between different levels of employees.

5. Talent Management: Career paths will shift from traditional frameworks to flexible, outcome-focused trajectories. AI-assisted performance management will promote innovation and collaboration within hybrid workflows.

6. Employee Experience and Culture: HR must foster a culture of engagement and meaning. Leveraging agentic AI for sentiment assessment will refine interventions, ensuring a positive workplace environment.

By taking a proactive approach, HR can harness agentic AI's potential, transforming talent acquisition, development, and engagement strategies for a resilient, competitive future. The organizations that thrive will harness HR's role in creating a co-intelligent workforce where humans and AI work together seamlessly to drive organizational success.