Teams | Collaboration | Customer Service | Project Management

The real advantage of using AI comes from teaming up, not just speeding up.

Mergers and acquisitions in 2026 are no longer defined only by financial integration — they are shaped by how quickly employees adapt to organizational change. When teams merge, workflows shift, reporting structures evolve, and productivity patterns fluctuate. Without visibility into these transitions, businesses risk operational slowdowns and employee disengagement.

The modern corporate landscape is currently navigating a fundamental shift in how work is conceptualized, executed, and measured across global boundaries. As organizations transition toward permanent hybrid and remote models, traditional methods of oversight—physical presence and manual check-ins—have proven insufficient for the digital era.

Endava is a leading provider of next-generation technology services with 11,000 full-time employees serving enterprise clients across multiple industries. At a time when many organizations are testing AI in pockets — a chatbot here, a model there — Endava recognized the business imperative of a holistic AI transformation strategy at a company-wide level.

As a cloud architect, you’re going to have to embrace AI as part of your job — unless handcrafted artisan cloud becomes a niche in the future. But this doesn’t mean that you’re going to be left by the wayside. Anybody who has used AI coding tools knows that interesting things can happen when decisions are left up to them. So, that means decision-making should be left up to the people and the code writing to the AI bots … right?

Picture this: You own a baby products eCommerce store and use AI to breakdown customer purchase habits and recommend products. The model automatically recommends related items, bundles items, and optimizes inventory ahead of demand spikes. Sales increase and stockouts reduce. At first, the model serves its purpose without hiccups. But then customers begin complaining about wrong gender item matches. You call in the expert only for them to realize that your training data is biased.

Support teams usually feel the pain first. The same questions keep coming in, new users get stuck in the same spots, and agents spend time repeating fixes that should be self serve. A strong knowledge base is one of the cheapest ways to reduce that load because it does two jobs at once. It helps customers solve problems quickly, and it pulls in high trust search traffic, since people tend to believe official help docs more than generic blog posts.

There are millions of macOS users around the world who use the system professionally. Likewise, accurate time tracking on these Apple devices is also crucial for accurate payroll processing, auditing, and client billing. Time tracking software for Mac users is the need of the hour. Written by: Sagar Modi.

SPI Research has proven that there’s a 7.7x difference in profitability between the most and least mature professional services firms. But nobody’s explained why that divide happens—until now. We surveyed 303 firms across the United Kingdom, United States, Australia, Canada, and beyond to find out. Their answers reveal where most firms are getting stuck. And what the top performers are doing differently.

In today’s digital workplace, information is both a powerful asset and a persistent challenge. Organizations generate more content than ever, yet employees often struggle to find what they need when they need it. Knowledge becomes trapped in disconnected systems. Teams duplicate work because they cannot locate existing documents. Critical insights remain hidden simply because the path to them is too fragmented. Search should bridge these silos.