Gone are the days when AI was used only for running optimization models, automating dashboards and reports, or handling manual middle-office tasks. The future of Agentic AI is already here.
A swarm of AI agents can analyze historical data, read files from SharePoint sites, prepare a list of promotions, and follow workflows that include a human-in-the-loop to validate recommendations. Agentic AI can also support volume planning, accruals, claims management, promotion planning, pricing decisions, and commercial reporting, while automating a significant share of repetitive middle-office work.
For business leaders, this creates a major opportunity: reducing manual resourcing needs while improving speed, personalization, productivity, and commercial performance.
This does not mean replacing every human role. The stronger model is a human–AI commercial operating model, where AI agents handle repetitive, data-heavy, and coordination-intensive work, while people focus on strategy, customer relationships, creativity, judgment, governance, and exception handling.
According to McKinsey, properly deployed AI agents can deliver 3% to 5% annual productivity improvement, with growth potential reaching 10% or more when companies scale agents effectively across workflows. McKinsey also highlights that the greatest impact comes when organizations redesign workflows around agents rather than simply adding AI to existing processes.
Many commercial organizations still operate with fragmented systems, manual processes, and high dependency on cross-functional coordination.
Common challenges include:
- Inefficient cross-team collaboration
- Inconsistent sales follow-ups
- High cost-to-serve
- Delayed pricing decisions
- Dependency on cross-functional teams for end-to-end commercial reporting
- Slow responsiveness to changes in market dynamics
These challenges impede organizational growth and lead to leakages, both in terms of resource effort and financial performance. Inefficient follow-ups, delayed decisions, weak tracking, and fragmented reporting can directly affect revenue realization and margin protection.
In today’s environment, where companies are managing global supply chain constraints, inflationary pressure, tariff uncertainty, and volatile demand patterns, these inefficiencies can bleed margins and reduce competitiveness. For many organizations, this is no longer affordable.
Consulting firms such as McKinsey, BCG, and Bain have consistently emphasized that companies must move beyond isolated automation and focus on AI-led workflow transformation, data readiness, governance, and responsible adoption. This is especially relevant for commercial functions, where speed, accuracy, and responsiveness directly influence revenue and profitability.
Agentic AI is not simply another technology upgrade. It is the foundation of a new commercial operating model.
Agentic AI transformation starts with an honest maturity assessment. To help organisations prepare for success, we’ve created a practical checklist-driven blog to evaluate readiness and identify what’s needed to scale with confidence. Please read our blog – Readiness Checklist for Agentic AI Transformation
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