In a landscape where AI is evolving from automation to autonomy, Deepak Ahluwalia, Founder & CEO at CoHyre.ai, in conversation with CIO&Leader, shared how the company is embedding AI into its core strategy to streamline HR processes and reshape the future of work and the workforce itself.
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CIO&Leader: The Salesforce report suggests a 383% rise in agentic AI adoption by 2027. How is your organization aligning its business and talent strategy to leverage this shift?
Deepak Ahluwalia: At CoHyre.ai, we see the 383% surge in agentic AI adoption not as a future trend but as a present imperative. We’re building a culture that blends the best of human potential with the precision of AI-driven decision-making. On the business side, our entire product strategy is oriented around an agentic AI framework, enabling autonomous, data-driven actions for talent acquisition and HR transformation. From a talent perspective, we’re actively investing in cross-disciplinary skill sets that integrate human judgment with AI co-piloting, empowering our teams to lead with data, not just intuition.
CIO&Leader: Agentic AI is seen not just as a tool but as a strategic lever. What are some high-impact business areas where you plan to deploy agentic AI in the next 12–24 months?
Deepak Ahluwalia: For us, agentic AI is the engine of hyper-productivity. Over the next 12–24 months, we’re deploying it across three high-impact areas:
Autonomous Talent Matching: Our proprietary “Aria” AI agents dynamically score candidates and orchestrate interviews, compressing hiring timelines from months to weeks.
Predictive Hiring Workflows: AI-led simulations of future team performance, helping companies hire for culture and capability, not just credentials.
Bias-Free Screening & Analytics: Real-time, autonomous auditing of hiring decisions to ensure inclusivity and reduce human bias at scale.
This approach ensures we’re not just automating processes, we’re creating intelligent systems that learn, adapt, and drive business outcomes.
CIO&Leader: How are you ensuring that the adoption of agentic AI is not just a technology initiative but a business transformation led by leadership across functions?
Deepak Ahluwalia: We believe agentic AI adoption must be championed by leadership, not delegated to IT alone. At CoHyre.ai, we’ve embedded AI fluency as a leadership competency, starting with our founding team and extending to every function. From product to customer success, every leader has a shared mandate: how can AI create tangible value for customers and stakeholders? This cross-functional alignment ensures agentic AI becomes a catalyst for transformation, not just a technology layer.
CIO&Leader: Despite ambitious plans, 88% of Indian firms haven’t implemented agentic AI yet. What are the key barriers your company faces in moving from intention to execution?
Deepak Ahluwalia: While the intent is widespread, the gap between vision and execution remains real, primarily due to data silos and organizational silos. For us, the key challenge has been integrating disparate data sources to train our agentic AI models effectively. We’ve addressed this by prioritizing data interoperability and building APIs that unlock value from HR systems, ATS platforms, and legacy databases. Another barrier is cultural, AI adoption requires shifting mindsets from linear, rules-based thinking to outcome-based experimentation.
CIO&Leader: With predictions of up to 25% workforce redeployment, how are you rethinking job roles, responsibilities, and career paths in the age of AI augmentation?
Deepak Ahluwalia: We see agentic AI not as a job destroyer but as a job shaper. At CoHyre.ai, we’re actively reimagining roles to emphasize problem-solving, empathy, and critical thinking, skills that complement AI’s analytical prowess. We’re investing in career pathways that pair human creativity with AI insights, whether that’s data-fluent HR specialists or AI-augmented recruiters. The future isn’t about replacement; it’s about amplification, making every employee exponentially more effective.
CIO&Leader: What steps are you taking to future-proof your workforce, reskilling, upskilling, or hiring, for a future where agentic AI becomes a co-worker, not a replacement?
Deepak Ahluwalia: Future-proofing is a daily priority. We’re embedding AI literacy across the company, through continuous learning modules, workshops, and exposure to live AI projects. We also view AI augmentation as a co-pilot model, equipping teams with intuitive interfaces that demystify AI’s inner workings and encourage experimentation. Hiring-wise, we’re focused on “T-shaped talent”, people with deep expertise in one domain and the curiosity to leverage AI tools across functions.
CIO&Leader: The report highlights potential productivity gains of over 40%. How are you measuring and realizing productivity improvements through AI in your business today?
Deepak Ahluwalia: We measure productivity not just in tasks completed but in outcomes achieved. With CoHyre’s agentic AI orchestration, we’ve already seen a 2–3x faster time-to-fill for customers, translating to direct revenue gains. Internally, we track three key metrics:
– Cycle Time Reduction – How quickly can a hiring workflow move from JD creation to offer?
– Quality of Hire – Are AI-identified candidates outperforming traditional shortlists?
– Human-Machine Collaboration Index – A measure of how well AI suggestions align with human judgment.
These metrics ensure that our AI deployments are not just about speed but about elevating decision quality and team effectiveness.
CIO&Leader: As agentic AI systems gain autonomy in decision-making, how are you approaching governance, ethics, and transparency to ensure responsible AI deployment?
Deepak Ahluwalia: Responsible AI isn’t optional, it’s foundational. We’ve built our governance model on three pillars:
- Explainability – Every AI decision in CoHyre’s platform is accompanied by a transparent reasoning layer, so stakeholders can understand “why,” not just “what.”
- Bias Mitigation – Continuous audits of model outputs for bias, ensuring fair and equitable hiring outcomes.
- Human-in-the-Loop Safeguards – AI doesn’t make final decisions alone; human reviewers validate and refine recommendations.
We also engage in ongoing dialogue with advisors and external experts to stress-test our frameworks, because responsible AI is a journey, not a destination.