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Insurance providers are not an exception in the data-thriving universe, and they have loads of data from claims processes, customer interactions, agents/partner sales. A McKinsey report says that the pace of technology evolution in the insurance industry seems rapid, with agents, customers, and insurers being data-driven for enhanced decision making, optimizing operations, and customer experience.
The core capabilities of decision intelligence include data models for connecting data sources, data prep, NLP-enabled search, automated insights, AutoML, sharing and making an impactful decision faster.
Organizations that focus on enhancing the employee experience, experience less employee turnover, high ROI, attract talent, and improved employee performance.
Augmented analytics are democratizing data and empowering businesses with faster time to actionable insights. But what’s augmented analytics? How does it help your business?
As we are integrating more digital channels into our enterprise ecosystems, the size and intricacy of business data are increasing. Extracting meaningful insights from this data has become complex.
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Intelligent Document Processing marks the ultimate convergence of OCR, Artificial Intelligence, and Machine Learning- a unified solution for advanced data processing. It involves data extraction from diverse sources, all managed on a unified platform.
Generative AI is widely accepted by users across the world. As gen AI evolves, we are exploring the business use cases for gen AI in various industries. Human resources management (HRM) is a key part of any business.
A survey by Capgemini found that 60% of business executives strongly advocated generative AI. Every industry – healthcare, manufacturing, banking, finance, etc., is tapping into the potential of generative AI technology. Retail, which is data-rich and touches customers’ lives directly, also finds some game-changing use cases for generative AI.
A survey by Capgemini found that 60% of business executives strongly advocated generative AI. Every industry – healthcare, manufacturing, banking, finance, etc., is tapping into the potential of generative AI technology. Retail, which is data-rich and touches customers’ lives directly, also finds some game-changing use cases for generative AI.
The manufacturing industry has already been using Artificial Intelligence (AI) since the fourth industrial revolution. Now, with the entry of generative AI in manufacturing, you have an opportunity to transform your back-office operations and drive business growth.
Do you know that the global Intelligent Document Processing (IDP) market is snowballing at a robust CAGR of 37.5%? The prime reason for this surge in IDP growth can be attributed to the critical need for enterprises to deal with substantial volumes of semi-structured and unstructured documents efficiently. Not just storing and accessing them securely but also facilitating the documents for advanced analytics.
If you asked any customer service professional to sum up their experience of the last couple of years, they would likely respond that it was intense! Implementing Artificial Intelligence in customer service is the right thing to do. With the buzz around generative AI models built on pre-trained, large language models that generate human-like, unique content based on prompts.
Retail is a data-rich industry. Retailers interact with millions of customers every year and produce huge volumes of data. Catering to the needs of these customers while being proactive in the highly competitive market is challenging. However, retailers can use data in their possession to their advantage by leveraging predictive analytics. Let us explore five major applications of predictive analytics in Retail.
Cloud adoption is a hot trend in the enterprise technology world. Businesses are moving from on-premises systems to cloud systems for flexibility, scalability, efficient process automation, robust data protection, and seamless remote collaboration.
To help you ensure a successful migration to the Azure cloud and develop quality applications, Microsoft offers Azure Cloud Adoption Framework (CAF) and Well-Architected Framework (WAF). In this article, let’s discuss Azure WAF – the five pillars and how implementing WAF helps your business.
Workforce management is a critical element in any enterprise. In such a rapidly changing global landscape, effective workforce management can be vital to the business’s success. Enterprises face a range of unique challenges that may call for innovative, out-of-the-box solutions.
Data-driven decision-making (DDDM) in a business is easier said than done. Your DDDM process should have two important characteristics – quality and speed. However, for most executives, making quality decisions faster is still a challenge.
Measuring the business value of Power Platform solutions is paramount as it offers insight into their contributions to overall organizational success.
The pace at which data is growing is exponential. With new data sources being created and connected, enterprises are overwhelmed with data management.
Manufacturing is fundamentally about innovation. It boosts economic capacity, strengthens workforces, and opens doors to progress and opportunities. Since the industrial revolution, a lot has changed, and the industry has become much more complicated.
Applied AI – the application of AI technology in business, is skyrocketing. An Accenture report on AI revealed that 84% of business executives believe that AI adoption would drive their business growth. Applied AI empowers businesses with end-to-end process automation and continuous process improvement for greater productivity and profitability.
Your upcoming workforce is Gen Z. Their views on work and the workplace are different from those of your existing workforce. They prioritize employee experience and job satisfaction more than compensation.
According to a Gartner survey, 60% of leaders in IT and D&A reported that their organizations embraced AI-generated synthetic data due to the challenges in real-world data accessibility. Further, 51% of the leaders cited that non-availability of data is driving the adoption.
Low-Code Solutions are transforming financial institutions by streamlining application development and enhancing customer experiences.
Data is the new gold in business. Explore how data estate modernization can help achieve goals, with better analytics, security, and flexibility.
Microsoft announced Copilot AI expansions at Microsoft Ignite 2023, enabling enterprises to transform operations. Explore the features and how you can leverage them.
Optimizing apps, automation, and data analytics with generative AI can supercharge business growth to new heights.
Master Data Management Solutions are often challenged with consolidation and structuring data across information silos.