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ZDNET’s key takeaways
- Only 15% of organizations have reached scaled multi-agentic orchestration.
- Most business leaders are reevaluating their business models in light of advances in agentic AI.
- Scaling agentic AI must begin with sufficient resources to transform the workforce.
Most US-based companies are under pressure and working hard to shift from experimenting with AI agents to deploying them in production, according to the latest research from Deloitte.
A survey of 501 senior business leaders involved in driving their companies’ AI strategies or implementations revealed that most organizations struggle to develop an executable, integrated roadmap for agentic AI initiatives. The survey found that 42% of organizations are testing small numbers of agents and 43% are expanding deployments of AI agents across functions. Only 15% of organizations have achieved scaled, orchestrated multi-agent deployments across customer service, IT, and engineering.
Also: Business adoption of AI agents tripled this year – as measurable ROI emerges
Business leaders must challenge their dominant logic
The question most business leaders struggle with is determining the viability of their business model and the impact of AI agents on existing processes and desired outcomes.
Nearly two-thirds of business leaders are reevaluating their business models due to advances in agentic AI. Half of the leaders have a clear view of their future operating model powered by AI agents. The challenges in scaling AI agent deployments include a lack of a unified, accessible data foundation (72%), an inability to trust and govern agents (70%), and the cost and complexity of integration (67%).
The other key challenge business leaders face with AI agents is that technological change is outpacing their organizations’ ability to adapt; this will continue to challenge businesses for the foreseeable future. Becoming an agentic enterprise is less about technology transformation and more about relational transformation.
Also: Why replacing staff with AI backfires – and 5 ways smart leaders generate real value instead
Only a few organizations said their business process and workflows are ready for agentic AI, including vision and strategy (36%), technology infrastructure (34%), data foundation (32%), and risk, security, and governance (26%). Only 1 in 5 businesses said their workforce is ready for agentic AI; a lack of employee reskilling and upskilling can be a major obstacle.
Becoming an agentic enterprise is more about relationships
Process and workflow transformation is key to scaling AI agents, and most business leaders are not ready. By 2030, 74% of business leaders noted that nearly half of business processes will be redesigned or rebuilt around AI agents. Sixty-one percent believe most of their processes will be powered by AI agents, and most of these agents will be largely autonomous, operating with little to no human involvement. The future will be autonomous, but as of now, only 16% of business leaders said their current processes are prepared for agentic adoption.
It is not a lack of ambition that is holding back organizations from scaling agentic AI. The challenge is poorly designed and misunderstood existing processes, a lack of access to trustworthy data and systems, and traditional ways of working. Another challenge businesses face is layering AI onto existing legacy processes rather than redesigning them from the ground up. The research found that layering can work, but process redesign should be a muscle that companies develop on their journey toward greater autonomy. Only 31% of businesses expect to redesign and rebuild their processes around AI agents by 2028, yet 74% expect changes by 2030.
Scaling agentic AI starts with investing in your workforce
Half of the leaders said their organizations are not investing enough in the workforce transformation efforts necessary for the successful adoption of AI agents. Leaders are expecting new roles and use cases where humans and AIs collaborate to co-create business value. Nearly half (43%) of business leaders anticipate major job disruption from agentic AI deployments, as routine and structured tasks become autonomous and are executed by AI agents.
The cost of training employees and tokens will introduce pressure on budgets, including unexpected expenses. Business leaders must become more cost-aware regarding infrastructure investments, employee readiness, and AI literacy, and the cost of redesigning processes to be agentic-led. The research found that 71% of organizations are currently working on baseline AI agent literacy, and 65% are working on upskilling and reskilling efforts for roles that could be affected by AI agents.
Also: ‘Specialists aren’t required’ anymore: How to stay valuable in an AI agent workplace today
The results of the survey show that investments in AI-ready infrastructure, data foundation, and employee AI literacy training are all key to scaling production deployments of AI agents. The key areas of consideration include: developing an integrated agentic roadmap; using AI agent layering as a bridge, not the destination; providing sufficient resources for workforce transformation; and defining your organization’s human-and-agent operating model.
The journey of becoming an agentic enterprise will require re-designing existing business processes, re-skilling your human labor to work differently, smartly and more efficiently, redeploying employees to work on less repetitive and less deterministic assignments, restructuring your organizational and financial models, re-claiming value creation opportunities that were ignored in the past, re-calibrating key performance metrics based on agentic usage (ex: tokens used to automate discrete work units), and finally re-mandating how leadership develops an autonomous focused vision, strategy and execution models.
