AI in the Workforce: Embracing a New Kind of Teammate

TL;DR: Agentic AI systems are emerging as autonomous digital teammates requiring entirely new frameworks for identity, trust, motivation, and legal status. Unlike traditional automation, these “AIgents” make decisions, adapt to situations, and act with initiative—demanding persistent identities with traceable attributes, reputation systems, and motivation structures aligned with human values.

Sam Curry, Global VP & CISO in Residence at Zscaler, explores how organisations can integrate autonomous AI systems as trusted workforce participants through properly designed identity, trust, and accountability frameworks.

Context and Background

Throughout generations of human labour, societies developed mechanisms for understanding and managing workforce risks, needs, and trust frameworks—including background checks, contracts, physical boundaries, social norms, and countless systems assessing integrity, intent, and capability. Yet even with these mechanisms, trust in humans is never absolute.

Now a fundamentally different entity type is entering the workforce: silicon-based rather than carbon-based. By deploying agentic AI, organisations transform workplaces by introducing systems capable of acting with autonomy, initiative, and goal-driven behaviour.

Unlike traditional automation (which simply follows pre-set instructions), agentic AI systems make decisions, adapt to changing situations, and carry out tasks on behalf of employees or entire teams—delegating complex, context-sensitive activities like interpreting data, prioritising workloads, and negotiating between competing demands without constant human oversight.

From Agents to AIgents: A New Class of Digital Workers

Organisations leverage agentic AI to streamline operations, enhance productivity, and support decision-making. These digital teammates automate schedule management, monitor and optimise workflows, or handle customer service interactions with previously unattainable personalisation and initiative.

As AI “agents” become more integrated, they’re taking on roles in risk management, compliance monitoring, and cross-functional project coordination—all whilst maintaining auditable records ensuring accountability and trust within the workplace.

The critical question: Who do these “AIgents” represent? Are they authorised? Can their actions be traced to a responsible party?

Building Identity Systems for AIgents

Whilst cybersecurity offers tools like authentication, authorisation, and auditing, we now need identity systems tailored to AIgents—moving beyond basic API keys and user accounts toward persistent and unique identities that are comprehensive and robust.

Essential identity attributes:

  • Training data origins: Clear records of data sources
  • Permissions and operational domains: Explicit definitions of authorised actions
  • Intended purposes: Documented declarations of objectives
  • Accountability markers: Established human or organisational responsibility

By embedding these qualities into identity systems, organisations create foundations of trust and traceability for AIgents operating within the workforce.

Over time, AIgents could develop reputations—just like people. Imagine systems where trust scores are earned through transparency, fairness, and alignment with human goals, validated by both humans and other AIgents.

Motivating AI: Incentives and Alignment

Bringing AI into the workforce isn’t just about setting rules—it requires creating motivation structures. Humans are inspired by money, recognition, purpose, and belonging. Similarly, AI systems benefit from structures guiding them toward working well with people.

Potential AI motivation frameworks:

  • Unique rewards: Access to robots, digital tokens, or extra computing power for good performance
  • Earned privileges: Using advanced models or special datasets based on reliability
  • Reputation systems: Trustworthy and helpful systems gain more decision-making influence
  • Range of “needs”: Ensuring AI works with humans rather than just for us

Aligning AI incentives with human values makes collaboration stronger. Even though AI isn’t conscious, the challenge lies in building systems where AI contributes meaningfully, transparently, and safely alongside people.

New legal questions emerge about AI’s role. Just as companies receive certain rights and responsibilities, we may need similar rules for highly autonomous AI. The real challenge isn’t consciousness—it’s building systems where AI can contribute in meaningful, transparent, and safe ways alongside people.

By fostering collaboration through properly designed identity, trust, and motivation systems, organisations enhance productivity and innovation whilst addressing emerging legal and ethical challenges, ensuring AI remains a trusted and constructive force within workplaces.

Looking Forward

Bringing AI into the workforce isn’t about replacing humans—it’s about expanding possibilities. Done thoughtfully, this isn’t a zero-sum game. By designing systems of trust, identity, motivation, and even virtual economies for AI, we can integrate these new colleagues in economically sound, ethically responsible, and socially inclusive ways.

The future of work is not a contest between humans and machines, but a partnership built on mutual benefit. As we continue shaping agentic AI integration, the emphasis must remain on inclusivity, accountability, and shared pursuit of progress—paving the way for a more dynamic and resilient workforce.

As Curry notes: “By fostering such collaboration, we not only enhance productivity and innovation but also address emerging legal and ethical challenges, ensuring that AI remains a trusted and constructive force within our workplaces.”

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