AI/ML
Gartner highlighted the six trends that will have a significant impact on infrastructure and operations (I&O) for 2025 ...
Being able to access the full potential of artificial intelligence (AI) and advanced analytics has become a critical differentiator for businesses. These technologies allow for more informed decision-making, boost operational efficiency, enhance security, and reveal valuable insights hidden within massive data sets. Yet, for organizations to truly harness AI's capabilities, they must first tap into an often-overlooked asset: their mainframe data ...
Embedding greater levels of deep learning into enterprise systems demands these deep-learning solutions to be "explainable," conveying to business users why it predicted what it predicted. This "explainability" needs to be communicated in an easy-to-understand and transparent manner to gain the comfort and confidence of users, building trust in the teams using these solutions and driving the adoption of a more responsible approach to development ...
In APMdigest's 2025 Predictions Series, industry experts offer predictions on how Observability and related technologies will evolve and impact business in 2025. Part 4 covers logs and Observability data ...
In APMdigest's 2025 Predictions Series, industry experts offer predictions on how Observability and related technologies will evolve and impact business in 2025. Part 3 covers OpenTelemetry, DevOps and more ...
In APMdigest's 2025 Predictions Series, industry experts offer predictions on how Observability and related technologies will evolve and impact business in 2025. Part 2 covers AI's impact on Observability, including AI Observability, AI-Powered Observability and AIOps ...
Generative AI represents more than just a technological advancement; it's a transformative shift in how businesses operate. Companies are beginning to tap into its ability to enhance processes, innovate products and improve customer experiences. According to a new IDC InfoBrief sponsored by Endava, 60% of CEOs globally highlight deploying AI, including generative AI, as their top modernization priority to support digital business ambitions over the next two years ...
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Technology leaders will invest in AI-driven customer experience (CX) strategies in the year ahead as they build more dynamic, relevant and meaningful connections with their target audiences ... As AI shifts the CX paradigm from reactive to proactive, tech leaders and their teams will embrace these five AI-driven strategies that will improve customer support and cybersecurity while providing smoother, more reliable service offerings ...
In the heat of the holiday online shopping rush, retailers face persistent challenges such as increased web traffic or cyber threats that can lead to high-impact outages. With profit margins under high pressure, retailers are prioritizing strategic investments to help drive business value while improving the customer experience ...
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In a fast-paced industry where customer service is a priority, the opportunity to use AI to personalize products and services, revolutionize delivery channels, and effectively manage peaks in demand such as Black Friday and Cyber Monday are vast. By leveraging AI to streamline demand forecasting, optimize inventory, personalize customer interactions, and adjust pricing, retailers can have a better handle on these stress points, and deliver a seamless digital experience ...
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New research from ServiceNow and ThoughtLab reveals that less than 30% of banks feel their transformation efforts are meeting evolving customer digital needs. Additionally, 52% say they must revamp their strategy to counter competition from outside the sector. Adapting to these challenges isn't just about staying competitive — it's about staying in business ...
Leaders in the financial services sector are bullish on AI, with 95% of business and IT decision makers saying that AI is a top C-Suite priority, and 96% of respondents believing it provides their business a competitive advantage, according to Riverbed's Global AI and Digital Experience Survey ...
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AI sure grew fast in popularity, but are AI apps any good? ... If companies are going to keep integrating AI applications into their tech stack at the rate they are, then they need to be aware of AI's limitations. More importantly, they need to evolve their testing regiment ...
Artificial intelligence (AI) is rapidly reshaping industries around the world. From optimizing business processes to unlocking new levels of innovation, AI is a critical driver of success for modern enterprises. As a result, business leaders — from DevOps engineers to CTOs — are under pressure to incorporate AI into their workflows to stay competitive. But the question isn't whether AI should be adopted — it's how ...
Half of all employees are using Shadow AI (i.e. non-company issued AI tools), according to a new report by Software AG ...
Operational resilience is an organization's ability to predict, respond to, and prevent unplanned work to drive reliable customer experiences and protect revenue. This doesn't just apply to downtime; it also covers service degradation due to latency or other factors. But make no mistake — when things go sideways, the bottom line and the customer are impacted ...
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Organizations continue to struggle to generate business value with AI. Despite increased investments in AI, only 34% of AI professionals feel fully equipped with the tools necessary to meet their organization's AI goals, according to The Unmet AI Needs Survey conducted by DataRobot ...
Organizations recognize the benefits of generative AI (GenAI) yet need help to implement the infrastructure necessary to deploy it, according to The Future of AI in IT Operations: Benefits and Challenges, a new report commissioned by ScienceLogic ...
All eyes are on the value AI can provide to enterprises. Whether it's simplifying the lives of developers, more accurately forecasting business decisions, or empowering teams to do more with less, AI has already become deeply integrated into businesses. However, it's still early to evaluate its impact using traditional methods. Here's how engineering and IT leaders can make educated decisions despite the ambiguity ...
The demand for real-time AI capabilities is pushing data scientists to develop and manage infrastructure that can handle massive volumes of data in motion. This includes streaming data pipelines, edge computing, scalable cloud architecture, and data quality and governance. These new responsibilities require data scientists to expand their skill sets significantly ...
40% of generative AI (GenAI) solutions will be multimodal (text, image, audio and video) by 2027, up from 1% in 2023, according to Gartner ...
As AI improves and strengthens various product innovations and technology functions, it's also influencing and infiltrating the observability space ... Observability helps translate technical stability into customer satisfaction and business success and AI amplifies this by driving continuous improvement at scale ...
Technical debt is a pressing issue for many organizations, stifling innovation and leading to costly inefficiencies ... Despite these challenges, 90% of IT leaders are planning to boost their spending on emerging technologies like AI in 2025 ... As budget season approaches, it's important for IT leaders to address technical debt to ensure that their 2025 budgets are allocated effectively and support successful technology adoption ...
As businesses and individuals increasingly seek to leverage artificial intelligence (AI), the cloud has become a critical enabler of AI's transformative power. Cloud platforms allow organizations to seamlessly scale their AI capabilities, hosting complex machine learning (ML) models while providing the flexibility needed to meet evolving business needs ... However, the promise of AI in the cloud brings significant challenges ...