Software leaders who are successfully using generative AI will tell you they aren’t doing it alone. AWS has been working with its independent software vendor customers to help them adopt and use generative AI to transform their business and reimagine their products and customer experiences. Together, we are navigating the rapidly changing landscape and turning ideas into solutions that deliver real business impact, so you can realize the full value of generative AI on AWS.

The software industry has witnessed explosive growth over the past several years, driven in large part by the disruptive potential of generative AI. Many believe it marks the start of the next super cycle, with the CAGR for enterprise spend on generative AI expected to be 140% over the next three years, compared to the 7% CAGR the software market has seen over the last eight years.i
All this spending on AI is coming from both new and reallocated budgets–37% of companies say they are allocating net new budget for generative AI; 60% say it will be coming from decreasing or cancelling other things within their existing IT budget; while 27% say it will come from decreasing or cancelling other non-IT budget items. This ebook

For decades, industrial digitalization has followed a familiar arc: more sensors, more dashboards, more reports, more data platforms, more visibility. The underlying assumption was simple: if only people could see more, they could do more. But the world has changed — and the data has outgrown us. The human cognitive bottleneck is now the limiting factor in industrial performance. Operators are drowning in dashboards. Engineers are trapped in manual reconciliations. Planners are stuck stitching Excel sheets onto legacy workflows and monolithic transaction systems with archaic business logic that were never designed for modern complexity. Decision cycles stretch from days to weeks, even as industrial systems change state in milliseconds.

The industrial sector faces a growing challenge: Operational data amassed over decades is scattered across multiple operational technology (OT), IT, and engineering systems, making it difficult to access, integrate, and use effectively. The complexity of data integration slows decision-making, limits innovation, and increases operational costs. To stay competitive, companies in asset-intensive industries like oil and gas, chemicals, and manufacturing need solutions that can unify and contextualize their data, turning it into actionable insights.

Organizations can develop new products, services, and business models faster than ever before. With the accelerated rate of innovation, business and IT leaders face mounting complexity from AI-driven technologies, distributed infrastructure,
and increasingly sophisticated AI-driven cyber threats.

Business and IT leaders acknowledge feeling caught between the imperative to innovate and the need for cyber resilience:

Die digitale Transformation ist längst Realität – besonders für mittelständische Unternehmen. Geschäftsmodelle basie ren zunehmend auf Cloud-Anwendun gen, Datenanalysen in Echtzeit, vernetz ten Produktionsprozessen und hybriden Arbeitsmodellen. All diese Entwicklungen sind massiv von stabilen und sicheren Netzwerken abhängig.

From AI assistants to AI agents: an innovation continuum

A key strength of GenAI is its capacity to adapt to a wide range of applications across diverse use cases with high impact results, with one of the most significant being the way that GenAI has transformed the pre-GenAI wave of AI assistants and chatbots. First wave AI assistants were rule-based and rely on
predefined workflows and preprogrammed responses and narrow natural language understanding (NLP). Their capabilities were typically limited to specific tasks like answering FAQs, executing simple commands, or retrieving predefined information. GenAI assistants, powered by sophisticated large
language models (LLMs), have improved traditional AI assistants by enabling them to better understand context and generate nuanced, human-like responses, often in near-real time. This makes GenAI assistants more versatile, and allows for more engaging, personalized multi-turn conversations.

AI continues to transform IT service management, enabling organizations to automate incident response, accelerate case resolution, and enhance support efficiency. Ready to discover which AI use cases deliver the greatest impact for your IT service desk operations? This comprehensive Gartner assessment provides the strategic insights you need to make informed decisions about AI implementation in your IT service desk Get your copy of Gartner® AI Use-Case Assessment for IT Service Desk to learn: Strategic AI Use Case Analysis: Compare multiple AI applications against business value and technical feasibility to prioritize your investments Implementation Roadmap: Understand how AI use cases progress through context, advice, and action stages for maximum impact Customizable Framework: Access the companion toolkit to tailor the use-case analysis for your organization’s specific needs and requirements Whether you’re just beginning to explore AI opportunities or looking to expand your current ITSM AI strategy, Gartner® ‘AI Use-Case Assessment for IT Service Desk’ provides a practical framework for driving long-term success.

Managing IT in today’s flexible work environment shouldn’t be complicated. The “Buyer’s Guide to All-in-One IT Support and Management” uncovers how a unified solution – like LogMeIn Resolve – can help you streamline your help desk, consolidate tools, boost productivity, and enhance security. With two decades of expertise supporting businesses from SMBs to enterprises, LogMeIn knows how to make IT hassle-free, from anywhere. Download this guide to discover the five key factors every SMB should consider when choosing a unified endpoint management and support solution, including core functionality, security, and dependability. See how LogMeIn’s all-in-one platform checks every box, empowering your business to do more with less and deliver exceptional support for today’s remote workforce.

Enterprises today are under intense pressure to modernize, migrate, and scale in the cloud—while keeping risk tightly under control. But hybrid and multi-cloud environments introduce complexity that legacy tools aren’t built to handle. As workloads shift, configurations drift, entitlements sprawl, and threats escalate, the consequences of cloud missteps—whether through misconfiguration, over-privilege, or unmonitored access—are increasingly business-critical. The threat landscape is equally unforgiving. From cloud ransomware and data exfiltration to lateral movement across services and identity privilege escalation—attackers now exploit the very elasticity and speed that make the cloud so appealing. Visibility gaps, fragmented datasets, and manual triage slow down response and open the door to breaches that could have been stopped. What’s needed is not another bolt-on security product, but an architectural shift: a consolidated, AI-powered, risk-first platform that makes cloud security manageable, efficient, and proactive. Download now to discover how a unified, AI-driven platform can help you stay ahead of cloud risk.