Chris Smith

Protecting AI Software and Enterprise Customers AI and emerging technology software are transforming business operations, but it also introduces unique risks. For software developers, these risks are not only technical, but they can also affect client operations, adoption, and trust. Enterprise customers often require assurances that software will remain maintainable, deployable, and secure, even if […]

Why Enterprise Trust Is a Critical Barrier in AI Software Sales AI and emerging technologies are moving from experimentation into enterprise production environments. For software developers, technical capability alone is no longer sufficient to secure enterprise adoption. Buyers must also be confident that the solution can be supported, maintained, and protected over time. Enterprise procurement,

Outsourcing software development and engaging in works-for-hire agreements are long-standing practices for enterprise organizations seeking flexibility, cost efficiency, and access to specialized expertise. While these models offer clear advantages, they also introduce traditional software risks that directly impact business continuity when vendor relationships change or end. For enterprise buyers, the primary concern is not whether

Modern manufacturing and industrial organizations depend heavily on specialized software to manage supply chains, production planning, logistics, quality control, and regulatory compliance. From ERP and MES platforms to supplier portals and custom-built applications, software is now deeply embedded in operational continuity. While these systems enable efficiency and scalability, they also introduce a critical risk that

Artificial intelligence is no longer an experimental capability reserved for innovation teams. Across industries, AI platforms now support revenue generation, customer engagement, risk analysis, and core operational decision making. As reliance on AI grows, so does the importance of selecting vendors that can support long-term business objectives without introducing unacceptable risk. For CIOs and enterprise

Enterprise organizations are under increasing pressure to manage third-party software risk while maintaining procurement velocity. Yet many teams still treat software escrow as an afterthought rather than a strategic control. The reality is straightforward. If a critical vendor fails, your operations, data access, and service continuity are immediately at risk. This is where structured escrow

Artificial intelligence is rapidly becoming embedded in enterprise operations, supporting functions that range from analytics and automation to customer engagement and decision support. As AI systems transition from experimental initiatives to mission-critical infrastructure, enterprise organizations face a growing set of risks that extend beyond traditional software concerns. AI and emerging technology risk encompasses operational dependency,

Artificial intelligence is rapidly becoming embedded in enterprise operations, supporting functions that range from analytics and automation to customer engagement and decision support. As AI systems transition from experimental initiatives to mission-critical infrastructure, enterprise organizations face a growing set of risks that extend beyond traditional software concerns. AI and emerging technology risk encompasses operational dependency,

Artificial intelligence has moved rapidly from experimentation to production deployment. What once lived in research environments or internal prototypes is now embedded in customer-facing applications, decision-making systems, and core business workflows. For software developers, this transition introduces a new category of risk that extends beyond traditional software concerns. AI and emerging technology risk encompasses more