HomeFuture of WorkDigital HRHR TechnologyWhy HR’s partnership with IT is mission critical for AI adoption

Why HR's partnership with IT is mission critical for AI adoption

  • 3 Min Read

As AI revolutionizes HR, partnering with IT is vital for mitigating risks, ensuring governance, and driving adoption of transformative new technologies.

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The AI revolution is already here, transforming how organizations operate across every business function. HR is no exception, with a recent Aptitude Research study finding 75% of companies are embedding artificial intelligence into their HR operating models.

While hugely promising for streamlining processes and unlocking new capabilities, the rise of AI also brings substantial risks around data privacy, security, ethics, and corporate governance.

As the guardians of an organization’s most precious asset – its workforce – HR teams must get ahead of the AI curve by partnering closely with their IT counterparts.

This cross-functional collaboration is vital for mitigating risks, ensuring compliance, and leveraging technology responsibly as AI permeates HR processes from recruitment and onboarding to performance management and retention.

No organizational function is more data-driven than HR, which routinely handles sensitive personal employee information. As AI ingests and analyzes this data, there are significant risks around data privacy, security, and ethical use that require robust risk management protocols.

HR and IT must work in lockstep developing rigorous data governance policies that establish clear guidelines on proper data handling, AI model training practices, and continuous monitoring for bias or ethical lapses. The credibility and legal standing of both functions are on the line.

Risks and Compliance in AI-Enhanced HR Operations

Adhering to Corporate Governance & Compliance Similarly, HR’s embrace of AI cannot occur in a governance vacuum. Close partnership with IT and other key stakeholders is necessary to ensure new AI systems conform to all relevant corporate policies, regulatory mandates, and industry best practices around issues like data retention, records management, and audit trails.

Existing organizational checks and balances must be adapted for machine learning, with rigorous testing and validation of AI systems’ decision-making. Compliance is not optional in highly regulated fields like healthcare and finance where HR increasingly utilizes AI.

Conducting Comprehensive Due Diligence

Rushing to adopt AI without extensive due diligence is a recipe for disaster. This is where partnering with an organization’s tech experts in IT becomes indispensable. Before rolling out any new AI/ML solution, joint HR-IT teams should exhaustively vet potential risks and shortcomings, pressure test performance under real-world conditions, and construct detailed contingency plans for responding to errors, biases, or system failures.

AI vendors’ claims must be scrutinized, and employee privacy impact assessments conducted – with IT’s cybersecurity lens helping head off potential data exposure.

Driving Adoption: Integrating AI in HR Processes

Moreover, beyond risk mitigation and governance, HR’s ability to successfully deploy AI solutions will hinge greatly on IT’s technical expertise and institutional knowledge. IT’s deep familiarity with existing data infrastructure, software integration challenges, and change management best practices will be invaluable for driving user adoption and project momentum once initiatives go live.

This symbiotic HR-IT relationship – long seen as critical for rolling out foundational HCM technologies – is even more paramount as data and AI become deeply embedded into HR’s future operating model.

The power of AI to transform HR is immense, but so are the potential pitfalls without the proper safeguards and strategic IT partnerships in place from the outset.

By responsibly co-developing and co-governing AI’s application to HR, these two functions can ensure its transformative potential is channelled safely and effectively, building trust and protecting employee interests as they evolve how work gets done.

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