How firms can overcome key AI adoption barriers

Two years after ChatGPT's launch, it's evident that all enterprises will eventually become Artificial Intelligence (AI) companies. While many recognise AI's transformative potential, most struggle with full adoption due to challenges in AI readiness. For example, an Infosys study from November reveals that although companies expect productivity gains of up to 40%, only 2% are prepared in critical areas like strategy, governance, talent, data, and technology.

Josh Jarrett, Senior Vice-President of AI Growth at publishing firm Wiley, pointed out issues such as security, privacy, ethics, and bias, along with a lack of necessary skills and tacit knowledge. He noted that while measurable factors like strategy and technology can be managed, addressing talent and cultural transformation is more complex.

To integrate AI effectively, organisations need a clear strategy that resonates with employees. A comprehensive AI approach aligned with business goals and strong governance is essential to mitigate risks like bias and security breaches, he mentioned.

Experts also highlight a significant gap in AI responsibility as a barrier for enterprises. Research by NTT Data and Jigsaw Research published in February indicates a divide among C-suite executives, which shows that one-third prioritise responsibility over innovation, another third favour innovation over safety, and the remaining third balance both. Additionally, unclear regulations hinder AI investment, with companies concerned about security risks and lacking responsible AI policies.

Moreover, Lenovo’s recent 2025 CIO Playbook highlights that proving the return on AI investments often remains challenging. Ashley Gorakhpurwalla, President, of Infrastructure Solutions Group, Lenovo believes that uncertain financial returns on these investments and gaps in organisational readiness often impede its adoption. “This tension is magnified by a disconnect between growing AI investments and pervasive doubts among decision-makers about its value,” he said.

NTT Data CEO Abhijit Dubey emphasised that AI must be developed responsibly from inception, incorporating security, compliance, and transparency. He urged leadership to strive for ethical standards while upskilling employees to collaborate with AI and understand its risks and opportunities.

Gautam Singh, Business Unit Head at WNS Analytics, also believes C-suite leaders must set the right tone for business heads, users, and AI developers. “Business leaders must set the right tone for business heads, users and AI developers in their organisations.  It is incumbent upon leaders to ensure that their AI initiatives uphold individual rights, liberties and preferences while fostering transparency and trust,” he said

As AI becomes more widespread, organisations must also navigate emerging legal challenges. Komal Gupta, Chief Innovation Officer at Cyril Amarchand Mangaldas opines that while lawmakers are working to create regulations addressing AI-related issues, effective communication and education about these legal vulnerabilities are crucial, as employee actions can expose risks.

To prepare the workforce for the future, organisations should aim for 100 per cent AI awareness among employees, focusing on explainability, fairness, security, and regulatory compliance. Gupta advocated for an AI-ready workforce that understands legal considerations like AI model licensing, dataset issues, and ownership of AI-generated content.

Nonetheless, forward-thinking companies are finding ways to overcome the various hurdles and reap the benefits of an AI investment. As Gorakhpurwalla recommends companies create an AI task force comprising leaders from different departments to ensure a holistic approach to implementation. AI is not just another IT project. It's a fundamental shift in how a business operates.

“To harness AI’s transformative power, organisations need a data-driven strategy that ensures scalability, interoperability, and tangible business outcomes,” he concluded.