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...
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Topics:
AI,
Generative AI,
AI and Machine Learning,
Machine Learning Operations,
Analytics and Data
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...
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Topics:
Data Intelligence,
Analytics and Data
I previously wrote about data mesh as a cultural and organizational approach to distributed data processing. Data mesh has four key principles—domain-oriented ownership, data as a product, self-serve data infrastructure and federated governance—each of which is being widely adopted. I assert that by 2027, more than 6 in 10 enterprises will adopt technologies to facilitate the delivery of data as a product as they adapt their cultural and organizational approaches to data ownership in the...
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Topics:
data operations,
Analytics and Data
As I’ve written recently, artificial intelligence governance is a concern for many enterprises. In our recent ISG Market Lens study on generative AI, 39% of participants cited data privacy and security among the biggest inhibitors to adopting AI. Nearly a third (32%) identified performance and quality (e.g., erroneous results), and an equal amount (32%) mentioned legal risk.
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Topics:
AI,
Generative AI,
AI and Machine Learning,
Machine Learning Operations,
Analytics and Data
As I explained in our recent Buyers Guide for Data Platforms, the popularization of generative artificial intelligence (GenAI) has had a significant impact on the requirements for data platforms in the last 18 months. While there is an ongoing need for data platforms to support data warehousing workloads involving analytic reports and dashboards, there is increasing demand for analytic data platform providers to add dedicated functionality for data engineering, including the development,...
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Topics:
Analytics,
natural language processing,
data platforms,
Generative AI,
AI and Machine Learning,
Model Building and Large Language Models,
Machine Learning Operations
The topic of skills is not new to the world of talent management or development, making many appearances in the talent conversation over the years. Recently, it has been a permanent fixture in the discussion, focusing on the total integration of skills across all aspects of the employee experience. The term “skills economy” describes the evolution of how value is assigned in the workplace and employment, emphasizing the importance of individual skills over traditional job credentials.
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Topics:
Human Capital Management,
Learning Management,
Talent Management,
Workforce Management,
Payroll Management,
Total Compensation Management,
employee experience
It is unfortunate that business-focused digital communications are sold under three different headings: Contact Center as a Service (CCaaS), Unified Communication as a Service (UCaaS) and Communication Platform as a Service (CPaaS). (And that just counts the cloud options—let us acknowledge the huge, continuing, installed base on premises.) These are terrible ways to describe complex, varied and overlapping offerings. What distinguishes them are:
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Topics:
Customer Engagement,
Customer Experience,
Contact Center,
Digital Communications,
Customer Experience Management,
CCaaS,
Intelligent Self-Service,
CXM,
UCaaS,
CPaaS
The final of the men’s 100 meters at the Paris Olympics this summer was a reminder that being successful requires not just being fast but performing at the right time. Being fast is obviously a prerequisite for participating in an Olympic 100-meter final, and all the competitors finished the race in under 10 seconds, with just 0.12 seconds separating the first man from the last. While all the athletes were fast, what separated the winner of the gold medal—USA’s Noah Lyles—was execution. He was ...
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Topics:
Streaming Data & Events,
Analytics and Data
Prophix launched its Prophix One platform earlier this year. CFOs of midsize enterprises should take a look at it because it supports a more effective approach to finance and accounting operations in growing companies. It facilitates the transition of organizations that can no longer make do with work-arounds of existing systems to those with formal, controlled core processes that can be completed faster with reduced risk. The platform performs financial consolidation, account reconciliation...
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Topics:
Office of Finance,
Business Planning,
ERP and Continuous Accounting,
digital finance,
AI and Machine Learning,
Consolidate and Close Management
Sage recently held an analyst summit to take a deeper dive into its product and technology roadmap, complementing sessions it held at its 2024 user group conference that I commented on earlier this year. ERP systems have been central to the operational and financial management of enterprises since they first appeared in the 1990s. They are so familiar that they have become part of the background and only noticeable when something fails. We are now in a major transition to a new era of...
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Topics:
Office of Finance,
ERP and Continuous Accounting