... AI’s popularity can lead to employees using it in creative ways that might violate policy and risk exfiltration of confidential data, threatening enterprise value and reputation. CISOs must define a robust program of education, monitoring and filtering to encourage innovation while mitigating shadow ...
Analyst(s): John Watts | Jeremy D'Hoinne | Andrew Walls
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... AI-native software engineering is disrupting traditional development processes as AI evolves from optional tool to essential collaborator. Product leaders must upgrade development environments, talent strategies and architectural approaches to maintain competitiveness in this rapidly evolving landscape ...
... Traditional provider-enterprise value relationships will not drive AI adoption. It is not sufficient to sell an AI tool and expect customers to make it valuable. In the intelligence supercycle, providers and enterprises need to create mutual value by working together to deliver target business outcomes ...
... AI-enabled physical security technologies are essential to counter the escalating threat environment and elevate risk management to predictive risk intelligence. Product leaders must accelerate investment in enabling technologies and tune roadmaps to exploit the AI race opportunity disrupting business ...
... AI will replace those who cannot convert expertise into tangible business benefits, forcing consulting providers to redefine themselves and their offerings. Tech services leaders must rapidly reinvent and reengage to remain relevant in an AI-driven market or risk being replaced. Overview Strategic Planning ...
... obsolescence if they do not successfully respond to Power BI’s dominance and AI-driven evolution. To drive adoption, chief product officers should bolster capabilities in adjacent areas like data quality and integration, agentic AI, decision intelligence and domain-specific use cases. Overview Analysis ...
Analyst(s): Radu Miclaus | Omar Ansari | Jim Hare | Kevin Quinn
... While service leaders aim to cut costs with AI chatbots, the complexity of natural language and inconsistency of GenAI outputs often undermine ROI. This research provides step-by-step guidance for combining manual testing with agentic AI and other AI-augmentation techniques to maximize chatbot ROI. ...
... Agentic AI is the key to business transformation as innovative insurers reengineer digital and customer experiences and deploy a hybrid workforce model that leverages AI agents with human-centric design. Insurance CIOs must optimize agentic AI use to prepare for organizational transformation. Insights ...
... Relying on AI to expand test coverage leads to missed defects, as AI-generated tests often lack depth and precision. To mitigate this risk, software engineers should use AI mutation testing, an emerging technique, to strengthen unit test effectiveness and deliver robust, reliable software. Overview ...