OPINION: Can AI agents and humans be colleagues?
In today’s workplaces, the drive for efficiency has led organisations to deploy enterprise software ranging from employee engagement to advanced analytics and collaboration platforms. But beneath all the dashboards and digital infrastructure lies a more fundamental challenge: Can humans and AI agents truly work as colleagues?
It’s one thing to invest in tools; it’s another to design applications where AI and humans complement, not compete with each other. When AI is underutilised and people operate in silos, the promise of collaborative intelligence fades, and so does an organisation’s agility.
Consider a customer support centre during peak season. Traditionally, human agents juggle ticket triage, knowledge-base searches, and issue escalations. Response times stretch, customers wait, and frustration builds. Now contrast that with a hybrid model: AI systems handle first-level queries, categorise cases by urgency and sentiment, and draft responses. Human agents step in only where nuance or critical thinking is needed, guided by AI-driven context and suggested actions. What once took hours now resolves in minutes. Metrics like first-contact resolution and customer satisfaction begin to shift measurably.
This is not a glimpse into the future; it’s already underway. According to a 2024 McKinsey report, 64 per cent of companies that integrate AI into CX see an ROI increase within 12 months. Still, many companies remain stuck in a mindset where AI is seen as a backend utility or standalone assistant rather than a true teammate.
The real shift requires thoughtful design. Clearly defined responsibilities are key: what the AI agent owns, where human intervention begins, and how handoffs are managed. This avoids overlapping efforts and builds confidence across the team.
Equally important is explainability. When an AI tool suggests a pricing adjustment or flags a customer churn risk, it shouldn’t just provide an output; it should offer context. A simple explanation like “renewal likelihood dropped due to unresolved service issues” enables human colleagues to act with clarity, not caution.
Learning must also be mutual. Organisations are beginning to implement feedback loops where outcomes are reviewed jointly by human teams and AI logs. These sessions help refine models, improve workflows, and foster a sense of shared ownership. AI systems learn from updated data; people learn from patterns and outcomes. The result is a smarter, more adaptive team over time.
That said, the path forward isn’t without challenges. Data inconsistencies, algorithmic bias, and resistance to change all pose real hurdles. Ethical considerations, too, are evolving as AI takes on more complex roles. But companies willing to navigate these carefully are seeing real value emerge: leaner operations, faster decision-making, and teams with more time to focus on high-impact work, empathy, strategy, and creativity.
Ultimately, the future of work isn’t shaped neither by AI alone, nor by human effort in isolation. It lies in a collaborative approach, humans and AI agents working in tandem, each amplifying the other’s strengths. Not just man and machine, but partners with a purpose.
Because in a world that’s moving faster than ever, the edge belongs to those who know how to work not just harder, but smarter, together. Businesses should realise that the AI revolution is no different from the internet one two decades ago.
Imtiaz Bellary is the Managing Director and Co-founder of Engati.
Opinions expressed in this article are those of the author and do not purport to reflect the opinions or views of THE WEEK.
Sci/Tech