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Summary

AI agents are increasingly integral to business operations, handling tasks from lead generation to financial reconciliation. However, without proper data infrastructure, these systems risk creating chaos rather than efficiency. Successful AI deployment hinges on robust data management, which is crucial for European SMBs aiming to remain competitive. Companies that fail to establish a unified data context may face contradictory outcomes and diminished trust.
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Full Article (AI)

AI agents are no longer confined to coding assistance or customer service; they are becoming integral to enterprise operations. The potential return on investment is significant, yet autonomy without alignment can lead to chaos. It's crucial for business leaders to establish the necessary groundwork now. The trend towards an agent-driven enterprise is unmistakable. AI agents are autonomously managing tasks from lead generation to supply chain optimization. A medium-sized company might deploy 4,000 agents, each influencing revenue and customer experience. However, many organizations are unprepared for this shift, finding it challenging to scale AI initiatives. The challenge lies in the reliability gap. Despite significant investments in AI, many companies report minimal gains. Leaders, however, have seen substantial revenue increases and cost reductions. The difference? These leaders have developed critical data infrastructure before scaling AI. To ensure reliability, consider four key areas: models, tools, context, and governance. For example, an agent ordering pizza involves the model interpreting the request, tools executing the action, context providing personalization, and governance ensuring the outcome. Each area can be a potential failure point. The issue is not with models but with data. Inconsistent and incomplete data hinders agent performance. Enterprises face data debt from scattered, siloed systems leading to misaligned data. Agents initially perform well but struggle as their numbers grow and inconsistencies multiply. To leverage AI effectively, companies must build unified data context and robust governance. Those who skip foundational work will face chaos and eroded trust. Successful companies have recognized data as essential infrastructure, enabling dependability in AI operations. For enterprises, the focus should be on data readiness. Is your organization prepared to support agent transformation with the right data foundation? Companies like Reltio offer solutions to unify core data, allowing agents to operate from a consistent business context. Agents will shape the future of enterprises. The key to leadership will be in mastering context intelligence, ensuring accurate and consistent information supports AI decision-making.
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Business Impact

European SMBs must embrace AI but focus on building a reliable data foundation. As AI agents become more autonomous, the quality of data they rely on will define their success. This shift requires SMBs to prioritize data integration and governance, ensuring every agent operates from accurate and consistent information.
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Interesting Facts

  • AI model capability has exponentially increased.
  • Inference costs have dropped by 900x in three years.
  • European SMBs can leverage AI for operational efficiency.
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Business Opportunities

AI offers SMBs the chance to streamline operations and enhance customer experiences. By investing in data management systems, SMBs can deploy AI agents effectively, gaining a competitive edge. This technology enables real-time decision-making and operational efficiency, crucial for growth in a rapidly evolving market.
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LAZYSOFT Recommendations

LAZYSOFT advises SMBs to adopt a data-first strategy for successful AI integration. Focus on creating a unified data platform that supports agentic AI by ensuring completeness and accuracy. This foundation will enable seamless automation and improved decision-making, ultimately driving business value and competitive advantage.