Category: Risk Management
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AI Coding Competencies: What Inspires Awe — and 5 Ways They Spark Dread
The rise of AI in coding has sparked awe and concern among developers. While AI tools like Claude and Codex enhance coding efficiency, experts fear issues such as trust in AI-generated code, security risks, and potential loss of coding discipline. Ultimately, developers must ensure rigorous reviews to mitigate these risks.
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Will Agentic AI Drive the Convergence of ITOps and SecOps
Sacolick discusses the evolving convergence of IT Operations (ITOps) and Security Operations (SecOps) driven by AI capabilities. While leaders emphasize the need for unified tools and data, significant organizational differences remain. Successful integration could enhance operational efficiency and security, but achieving true convergence poses challenges, necessitating strong leadership and strategic alignment.
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3 Breakthrough Capabilities Uniting IT Ops, SecOps, and Data Governance
IT Ops, SecOps, and data governance teams face challenges as AI integration accelerates. At recent conferences, Collibra showcased data catalogs as centralized products, Tanium introduced zero-trust admin access with Jump Gate, and Commvault emphasized seamless multicloud recoveries. These innovations promote collaboration, address operational gaps, and enhance organizational resilience.
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How and Why to Create an Agile Risk Registry in Jira or Azure DevOps
Agile methodologies like Scrum enhance team focus on short-term priorities, but they lack a formal mechanism for discussing risks in releases. A risk registry can be vital for capturing and managing potential issues around project delivery and operational efficacy. Effective management of these risks can significantly improve agile outcomes across teams.
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Data Privacy Week: How Every CIO and CDO Must Take Control of Their Data
Data Privacy Week 2025 emphasizes the theme “Take control of your data.” Organizations are urged to enhance data governance and security in light of increasing risks from breaches and regulations holding leaders accountable. Key areas to focus on include human factors, data security, and AI governance to mitigate risks effectively.
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This Most Boring Gen AI Use Case Saves Millions in Regulated Industries
By 2025, generative AI will drive significant business value, focusing on practical, less glamorous use cases like document processing, intelligent automation, and AI agents. These advancements promise to increase accuracy and reduce costs, particularly in regulated industries like financial services, insurance, and life sciences. Private AI implementation within secure environments will be essential for maximizing…
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From Gray Work to Growth: Enabling Pragmatic AI in Construction and Manufacturing
The construction and manufacturing sectors are experiencing growth, with significant job additions and positive production forecasts. However, they face complexity due to multiple stakeholders, low margins, and evolving regulations. Utilizing dynamic work management and pragmatic AI can streamline operations and address inefficiencies, ultimately enhancing productivity and safety in these industries.
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3 Ways Empowering Tech Helps Construction Companies Attract Top Talent
Construction companies face an aging workforce and struggle attracting new talent. How commiting to tech, mobile, AI, and safety, turns this around.
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How Digital Trailblazer CIOs Avoid the Devastating ERP Upgrade
Opinions on SAP Sapphire 2024 by Isaac Sacolick on how Digital Trailblazer CIOs can transform to standard and migrate to cloud ERP.
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5 Decisive Questions to Ask Your Managed Security Services Provider (MSSP)
MSSPs are a power force multiplier for improving security, addressing incidents, and reducing vulnerabilities. Sacolick shares five decisive questions
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5 Practical Technologies Every Ambitious SMB in Industrials Should POC
Manufacturing and construction companies can benefit from no-code, computer vision, and IoT technologies. Star by finding the Digital Trailblazers.
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3 Key Risks to Address to Safely Experiment with Generative AI
Data, guardrails, and communications are key areas to develop generative AI, LLM, and ChatGPT risk mitigation strategies.