Which talent issues pose the greatest risk to executing your strategy? Attracting specialized skills, retaining top performers, building AI capabilities at scale, or succession planning for critical roles? Or something else?

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Chief Information Officer in Healthcare and Biotech17 hours ago

Our organization has grown through acquisition, bringing in both people and platforms. Some of these platforms have been developed over a 20-year period, and in many cases, subject matter expertise is concentrated in just one or two key individuals. This creates a risk, as those people become essential for anything related to those platforms, leading to bottlenecks and challenges in distributing knowledge more broadly. While this is something we can address over time, it does introduce risk and can slow progress. Aside from that, we do not see significant talent risks. We are fortunate to have a strong culture, offer fully remote work, and provide unlimited PTO, which helps us attract and retain the talent we need. We have found a good balance between accountability and opportunity, so attrition and attraction are not concerns for us, but we do have a lot of work to do.

VP of IT in Manufacturing17 hours ago

All of the above are relevant for us. As a smaller company with a significant investment in technology, our greatest challenge is finding the so-called unicorns, individuals who possess a broad range of specialized skills and can cover entire areas on their own. Unlike larger organizations that can have three or four people with overlapping skills, we often need a single person who can dive deep and manage everything in a particular domain. This creates a network of strong individual contributors, supported by a mix of external partners who can provide depth when needed. Our biggest challenge is finding the right balance and mix of internal and external resources who can work together effectively.

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Determine product vision and roadmap14%

Orchestrate AI agents and tools to deliver software autonomously46%

Build AI/ML powered solutions for end users54%

Ground AI models with RAG and other techniques29%

Design guardrails and guidelines for ethical and secure use of AI43%

Build and manage robust AI pipelines and automate deployment18%

Scale and automate common AI capabilities and engineering tools 21%

Co-develop software solutions directly with business and customer teams18%

Design solution architecture 14%

Deploy and monitor AI models7%

Something else – share in comments

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To automate routine tasks and workflows (e.g., scheduling, data entry, basic customer/patient service inquiries)27%

To enhance decision-making through advanced analytics and insights generation (e.g., risk assessment, market forecasting)45%

To create new products, services, or customer/patient experiences (e.g., personalized recommendations, virtual assistants)19%

To improve cybersecurity and fraud detection (e.g., threat analysis, anomaly detection)8%

We are not currently planning to implement AI agents within the next 12-18 months

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