A recent global study has revealed a notable disconnect between organisations’ ongoing experimentation with artificial intelligence (AI) and their readiness for full-scale enterprise deployment.
The research, ‘Practical Insights from AI Leaders’ and conducted by Kore.ai, surveyed 1,000 senior business and technology leaders across ten countries. While a significant majority — 71% — are actively using or piloting AI, only around 30% feel prepared to fully harness its potential within their organisations.
The report underscores a strong enthusiasm for increased AI investment, with 89% of respondents planning to escalate their organisational AI spend in 2025. Moreover, about three-quarters of companies intend to allocate up to half of their IT budgets to AI initiatives next year, reflecting a clear desire to deepen AI integration. However, despite these positive investment intentions, several barriers hinder widespread scaling. Chief among these are a shortage of AI talent, cited by 44% of respondents, unpredictable costs associated with large language models (42%), and ongoing concerns around data privacy and regulatory compliance (41%).
To address these challenges, leaders are prioritising key investment areas, including hiring both internal and external AI talent (66%), improving data quality (51%), enhancing solution security (40%), and upgrading IT infrastructure (37%). The report suggests that focusing on these domains will be crucial for achieving sustainable, organisation-wide AI impact.
The study also indicates a strategic shift away from building bespoke AI solutions from scratch. Instead, 72% of organisations favour purchasing and customised integration of existing AI tools, citing benefits such as ease of deployment, compliance, and better compatibility with existing systems. Technologies like generative AI, large language models, and conversational AI are already in production or early scaling phases, while emerging areas such as multi-modal AI, retrieval augmented generation (RAG), agent orchestration, and agentic AI are still in experimental stages.
Kore.ai’s Founder and CEO, Raj Koneru, emphasised that AI is no longer merely experimental but now a foundational element of business operations. He highlighted that organisations are reimagining their processes, driven by AI’s potential to innovate and grow. Koneru stressed the importance of data readiness, scalable infrastructure, responsible governance, and workforce empowerment to thrive alongside AI in an increasingly automated future.
Leaders surveyed also stressed that measuring return on investment (ROI) is vital to guiding AI strategies. The top indicators of AI project success identified included operational efficiency, quality of output, employee productivity, customer satisfaction, and reduced time-to-completion. Currently, the most common AI applications within organisations are business process orchestration — covering automation, compliance, and risk management — followed by workforce productivity enhancements and improvements in customer support and self-service.
Although 71% of companies are experimenting with or implementing AI across various departments, the study suggests that a clear enterprise-wide strategy, with a focus on the most beneficial processes, significantly increases the likelihood of transitioning from initial experiments to full deployment.
