Artificial Intelligence (AI) and Generative AI (GenAI) are no longer futuristic concepts but integral tools driving innovation and efficiency across industries.This report sheds light on the current state of AI adoption, highlighting the progress, challenges, and future trajectory of these technologies. The findings reveal a steady advancement in AI maturity, with organizations leveraging AI to transform decision-making, enhance customer experiences, and optimize operations. However, hurdles such as data silos and inconsistent data landscapes continue to impede progress, underscoring the need for strategic investments in data infrastructure and governance.
Key Highlights:
AI/GenAI Adoption Trends:
- 47% of respondents state that finance functions in their organizations have adopted AI/GenAI based tools, with 53% of respondents planning adoption within the next year.
- In comparison, 33% of the respondents state that Supply chain functions in their organizations are currently using AI/GenAI platforms, with 30% of the respondents planning adoption in the near term.
Decision Intelligence Maturity:
- 37% of the respondents claim that their organizations still have very traditional setups with dashboards based decision making. Whereas another 37% of the respondents claim that their organisation has capability of advanced AI driven decision-making. This highlights varying levels of AI maturity across organisations.
Function-Specific Aspirations:
- Customer Service 67% lead AI adoption aspirations, followed by Operations 57% and Sales 53%.
Development vs. Procurement:
- 50% have dedicated teams for internal platform development, while only 7% prefer fully external solutions, reflecting a strong focus on in-house innovation
AI Adoption Across Industries: A Mixed Landscape
The report underscores the varying pace of AI adoption across industries, with marketing and customer service emerging as the frontrunners. These functions are leveraging AI to personalize customer interactions, automate repetitive tasks, and gain actionable insights from vast datasets. In the finance sector, nearly half of the respondents have already adopted AI and GenAI tools, with a particular focus on forecasting and scenario planning. This reflects the sector’s emphasis on data-driven decision-making and risk management. The rapid adoption of AI in finance is expected to accelerate further, driven by the urgency of digital transformation and the need to stay competitive in a rapidly evolving landscape.
While AI adoption in supply chain management remains relatively low, the report identifies significant interest in areas such as inventory planning and risk analytics. These domains are poised for growth as organizations recognize the potential of AI to enhance supply chain resilience, optimize inventory levels, and mitigate risks. The growing interest in these applications signals a shift toward more strategic and proactive supply chain management, enabled by AI-driven insights.
Custom AI Platforms and GenAI Solutions: Diverse Implementation Strategies
One of the key trends highlighted in this report is the preference for custom AI platforms. Organizations are increasingly opting to develop tailored AI solutions that align with their unique needs and objectives. This approach not only allows for greater flexibility and control but also contributes to building proprietary intellectual property (IP). However, the complexity of GenAI solutions has led many companies to seek support from specialized service providers. This dual strategy of developing in-house capabilities while collaborating with external experts reflects the diverse approaches organizations are taking to implement AI effectively.
Platform Preferences: Explainability, Integration, and Scalability
When it comes to selecting AI platforms, organizations prioritize factors such as explainability, integration, and scalability. Explainability is critical for building trust in AI-generated insights, particularly in industries where decision-making carries significant consequences. Seamless integration with existing systems and the ability to scale solutions across the organization are also top considerations. Additionally, this report emphasizes the importance of rapid deployment, as organizations seek to quickly realize the benefits of AI investments.
The Future of AI: Central to Strategic Decision-Making
Looking ahead, nearly half of the respondents view AI as central to strategic decision-making. This reflects a growing recognition of AI’s potential to drive innovation, improve efficiency, and create competitive advantages. The preference for self-reliant AI deployments further underscores the desire to build proprietary capabilities and reduce dependency on external vendors. As organizations continue to mature in their AI journeys, the focus will shift toward developing robust AI ecosystems that integrate seamlessly with business processes and contribute to long-term value creation.
For the Full Report
For a detailed analysis, including industry benchmarks and best practices, check the full report here:
Aays is a leading AI and data consultancy transforming finance and supply chain for global enterprises. Since 2018, they have helped Fortune 1000 and high-growth companies solve complex challenges by integrating advanced AI and data driven technologies. With deep functional expertise, they enable organizations to drive meaningful, data-led decisions at scale.
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