Analyst Perspectives

Generative AI (GenAI) software can transform various aspects of enterprise operations, which makes it a critical component of modern business strategies. GenAI tools can automate repetitive tasks such as data entry, report generation and customer interactions. GenAI can improve overall operational efficiency, resulting in time and cost savings for the organization. Another benefit from GenAI software is the ability to analyze vast amounts of data and extract actionable insights, enhancing...

Oracle announced significant updates to its Fusion Cloud Supply Chain & Manufacturing (SCM) software at the recently held Oracle Cloud World. The application suite includes procurement, inventory management, warehouse management, order management and transportation management. SCM tasks are mostly small-scale and repetitive, yet the processes they support are far from simple. They involve the intricate choreography of often complex activities that require the accurate communication and...

With a flood of artificial intelligence-related tools now available for contact center buyers, it can be helpful to take a step back and review where buyers can expect a quick return on investment and maximum improvement in efficiency and productivity. For now, it appears that there are three broad buckets into which contact center-focused AI applications are clustered. They all relate to agent behavior and activity, including:

Although the terms data fabric and data mesh are often used interchangeably, I previously explained that they are distinct but complementary. Data fabric refers to technology products that can be used to integrate, manage and govern data across distributed environments, supporting the cultural and organizational data ownership and access goals of data mesh. Data fabric and data mesh are also both related to logical data management, which is the approach of providing virtualized access to data...

In a previous role I was actively involved with identifying and implementing dashboards and reports tracking key sales department metrics and KPIs for enterprise-size customers as well as high-tech growth companies. These included recognizable examples such as opportunity conversion rate, average deal size and sales velocity (length of time to close, won or lost). Wind the clock forward and in my role as an industry analyst I now talk to customers and have a wider view of the market.

Sprinklr’s analyst day in September was an opportunity for the company to dive deeply into its progress in pivoting its product offerings to align with a broader perception of the market for contact centers and adjacent customer-related applications.

As I noted in the 2024 Buyers Guide for Operational Data Platforms, intelligent applications powered by artificial intelligence have impacted the requirements for operational data platforms. These applications, infused with contextually relevant recommendations, predictions and forecasting, are driven by machine learning and generative AI.

Artificial intelligence-enabled business applications have advanced considerably over the past year as software providers have added a steady stream of capabilities. This includes customer facing, financial, supply chain and workforce software. ISG Research asserts that by 2027, almost all providers of business applications will use some form of generative AI to enhance capabilities and functionality to remain competitive.

In today's rapidly evolving technological landscape, artificial intelligence (AI) governance has emerged as a critical ingredient for successful AI deployments. It helps build trust in the results of AI models, it helps ensure compliance with regulations and it is necessary to meet internal governance requirements. Effective AI governance must encompass various dimensions, including data privacy, model drift, hallucinations, toxicity and perhaps most importantly, bias. Unfortunately, we expect...

As I recently noted, the term “data intelligence” has been used by multiple providers across analytics and data for several years and is becoming more widespread as software providers respond to the need to provide enterprises with a holistic view of data production and consumption. I assert that through 2027, three-quarters of enterprises will be engaged in data intelligence initiatives to increase trust in their data by leveraging metadata to understand how, when and where data is used in...