Today, Infor announces the selection of Amazon Bedrock, a service for building and scaling generative applications, to deploy GenAI solutions embedded within Infor CloudSuite designed to accelerate customer value. This further deepens Infor’s 11-year relationship with Amazon Web Services (AWS) and the close collaboration and success the companies share after years of extending Infor solutions through AWS services. Per the press release, Infor has built industry-specific use cases on AWS technology that allows their customers to complete daily tasks faster with pre-trained models built on Amazon Bedrock. Infor CTO comments, “Infor is on a mission to democratize AI by making it accessible to all our customers, regardless of the size of their organization or the technical resources they employ. Our goal is to build products that deliver transformative technologies directly to those who benefit most – the front-line people using Infor solutions. At Infor, we believe that merely giving customers the tools to apply GenAI isn’t enough. Our Industry AI approach combines both the tools and deep industry capability and expertise to collaboratively work with customers to build and offer solutions that drive real value.” Furthermore, Infor has released hundreds of proven predictive and prescriptive AI solutions through its Augmented Intelligence Service, helping customers to drive operational efficiencies, grow revenue, enhance customer satisfaction and predict future demand, all built using AWS services such as Amazon SageMaker. With Amazon Bedrock at the core of its generative AI innovations, customers will now have access to 60 additional use cases by year end.

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Effective data management is a high priority necessity for any business. The type of vigilance needed for data management include continuous monitoring, strict access control and security protocols and unwavering data quality itself. Pragyansmita Nayak, chief data scientist for Hitachi Vantara Federal, shares an article on Federal News Network highlighting four key ways that agencies can enhance their data governance practices.

Strategic data collection and continuous monitoring. “Federal agencies should clearly define their data objectives to ensure purpose-driven gathering, while preventing the challenges of aimless accumulation. They should prioritize the development of comprehensive data strategies that define collection goals, establish priorities, and implement efficient data management systems. This ensures that only relevant and high-quality data is collected and processed. Implementing continuous monitoring is crucial in this context, acting as a vigilant supervisor that promptly identifies and addresses any anomalies or inefficiencies in data management.”

Prioritize data quality for effective governance. “Federal agencies must prioritize data quality as a core element of their data management strategies. Assigning data stewards to oversee specific datasets further strengthens data integrity. High standards for data accuracy and reliability, along with enforcement measures, are essential. This commitment to excellence in data management ensures that governance remains a top priority.”

Promoting a culture of vigilance. “It’s critical for agency leadership to set a clear tone, emphasizing the importance of data security and integrity throughout every level of the agency. Fostering a continuous improvement mindset cultivates a proactive approach to data governance.”

Safeguarding data for effective management. “The importance of effective data management transcends seasonal boundaries. As we embrace the digital future, let our commitment to data stewardship be as enduring as the changing seasons, ensuring a secure and prosperous tomorrow for all.”

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Modern enterprise resource planning (ERP) systems these days are highly customizable, and many companies pain them with additional technologies to get the best from their systems. Two such technologies that can strengthen your ERP are artificial intelligence (AI) and Machine Learning. Vikram Bhandari, Chief Technology and Innovation Officer at Riveron, shares an article on Dataquest highlighting the benefits of AI and machine learning when paired with your enterprise’s ERP systems. Bhandari explains that AI evaluates the data processed by ERP systems to forecast and automate tasks. Meanwhile, Machine Learning establishes an automated machine interaction with ERP systems to ensure simultaneous targeted adjustments. ERP systems equipped with AI chatbots can offer personalized customer management service through Natural Language Processing (NLP) technology, enabling businesses to foster customer popularity, boosting conversion rate and customer satisfaction. In addition, Machine Learning algorithms help innovative systems to empower businesses to prepare for market fluctuations by anticipating them beforehand. Bhandari states that the useful data generated by AI and Machine Learning integrated systems help business executives to make informed decisions, reducing the reliance on improvising and bolstering profitability. It is important to note that while AI and machine learning bring a competitive advantage to enterprises, there are some challenges that come with it. Mainly, implementing and training your employees with this new technology.

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