The AI Executive Brief - Issue #12
Week of December 15, 2025
Executive Snapshot
The news this week demonstrated the momentum behind new types of agentic intelligence. This means, highly capable AIs that can act independently to carry out intricate and sophisticated tasks for their users. The tremendous growth we are witnessing with Nvidia’s Blackwell technology has increased the market values of technology companies significantly, and has also had a profound impact on how enterprises operate and interface with their customers. Environmental concerns have also been brought to the forefront, with studies indicating that the global emissions from artificial intelligence will reach upwards of 80 million tons of CO2 by 2025, which has led to increased calls for more sustainable infrastructure and for governments to enforce stricter regulations regarding the development and deployment of AI. Developments in new Multimodal AI Tools such as Google’s Gemini 3 Flash and MIT’s new furniture assembly robots also show the continually expanding role and breadth of Artificial Intelligence in both creative and physical capacities, as well as the continuing need for ethical guidelines and oversight regarding the deployment of AI, particularly with respect to the potential displacement of workers.
Strategic Deep Dive
The most pivotal advancement this week was the mainstreaming of agentic AI, marking a transition from conversational models to autonomous systems capable of independent action and decision-making. As noted in McKinsey’s 2025 State of AI survey and Microsoft’s Ignite announcements, agentic AI, exemplified by tools like Google’s Gemini agents and emerging platforms from startups like Databricks, enables workflows that handle multi-hour tasks, from code vulnerability fixes to supply chain optimization. Business implications include enhanced efficiency, with potential ROI gains of 20-30% in sectors like manufacturing and logistics, but competitive dynamics are shifting: incumbents like Amazon and Meta are accelerating deployments to avoid disruption, while open-source alternatives from China challenge U.S. dominance, potentially fragmenting global standards.
Operationally, risks abound, AI-assisted cyberattacks via darknet tools like DIG AI highlight vulnerabilities in ungoverned systems, and energy demands could strain power grids, as IMF analyses warn of a “resource race” for chips and minerals.
To guide planning, executives can adopt a “Agent Readiness Framework”: (1) Assess current processes for automation potential using metrics like task duration and repeatability; (2) Pilot hybrid human-AI teams with built-in observability layers for security and bias detection; (3) Scale via phased integration, targeting 15-20% cost reductions in Year 1 while allocating 10% of AI budgets to ethical audits. This model not only mitigates risks like data breaches but unlocks value creation through adaptive innovation, positioning firms to capture a share of the projected $20 billion in agent-driven revenues by late 2026.
A lesser-manifested trend associated with AI is the environmental effects of AI as described in a recent report with estimates of AI 2025 GHG emissions equal to that of many mid-sized countries. This has implications on the operating costs and thus will have an impact on operational cost increases. This could lead to a potential increase of 15-25% to AI systems due to the rising energy bills of operating Green Tech companies through renewable powered data centres. Regulators have expressed concerns about the risks of regulatory backlash against AI in educational applications, resulting in calls for bans of AI in education to maintain human based systems. A Sustainability Integration Model developed for AI contains the following components: (1) Mapping of AI Energy Consumption using carbon management tools; (2) Optimising AI Performance with Efficient AI Model Types i.e., by using alternative Small Language Models are able to reduce computational load by 10x; (3) Forming partnerships to provide green infrastructure to achieve net zero operations by 2028. This model will create long term value for organisations that align their sustainability strategies with Stakeholders requirements for responsible growth and as a result the potential for 10-15% premium valuations for Eco-Aligned Companies.
Leadership Action Playbook
Audit and Prioritize Agentic Deployments: Conduct a 30-day internal review to identify rote tasks suitable for agentic AI, starting with low-risk areas like data analysis or content generation; allocate 5-10% of Q1 2026 budgets to pilot programs with vendors like Microsoft Fabric or Google Gemini, ensuring measurable KPIs for productivity gains.
Embed Sustainability Metrics: Integrate CO2 tracking into all AI initiatives, targeting a 20% reduction in energy use through open-source models and renewable partnerships; form cross-functional teams to benchmark against industry peers and prepare for potential emissions regulations.
Enhance Governance and Risk Mitigation: Establish an AI ethics board to oversee deployments, incorporating tools for observability and bias detection; invest in upskilling programs to transition employees toward oversight roles, mitigating displacement while building organizational resilience.
Foster Innovation Ecosystems: Collaborate with startups via accelerators or investments in multimodal AI (e.g., video and robotics), aiming to co-develop custom agents; monitor geopolitical shifts, such as U.S.-China chip dynamics, to diversify supply chains and secure competitive advantages.
Monitor Emerging Trends: Track 2026 predictions from sources like Stanford HAI, preparing contingency plans for AGI advancements; experiment with AI in creative workflows, like viral ad generation, to capture early market share in consumer-facing applications.
Executive Perspective
As we close 2025, the week’s developments crystallize AI’s dual-edged promise: agentic systems offer unprecedented leverage for strategic agility, yet their unchecked growth risks amplifying inequalities and ecological strains, demanding leaders who view technology not as an end but as a means to humane progress. In my view, the true test of leadership lies in rejecting hype-driven overreach, evident in the year’s “hype correction”, and instead cultivating balanced ecosystems where AI augments human potential without eroding it, ensuring long-term strategies prioritize ethical stewardship over short-term gains. Ultimately, AI’s trajectory will reflect our choices: will we harness it to build resilient, inclusive futures, or allow it to deepen divides? The answer hinges on executives who lead with foresight, turning today’s insights into tomorrow’s enduring value.