As organizations expand their use of artificial intelligence, the skills they seek in independent talent are evolving. Executives increasingly distinguish between AI-direct skills—using AI to complete tasks or projects—and AI-adjacent skills, which help organizations apply the technology safely, responsibly and effectively.
Our 2026 State of Independence report, based on interviews with business leaders across a variety of industries, examines which capabilities organizations expect to become more important as AI adoption grows. The findings make clear that knowing how to use AI is only part of the equation: Companies also need professionals who can align AI with business goals and apply specialized expertise.
AI tools are becoming more accessible but knowing how to use them is not the same as knowing how to apply them to a specific business challenge. Organizations need professionals who can connect AI capabilities to business goals and deliver measurable results.
The ability to combine business knowledge with AI fluency was the most frequently selected capability in our survey, cited by 53% of respondents.
Independent professionals may be especially well positioned to succeed in these efforts. Working across multiple organizations exposes them to a range of AI tools, workflows and implementation strategies. They can then bring those insights to new engagements—helping clients apply lessons learned elsewhere and avoid starting from square one each time.
Next on this list: Technical AI expertise was selected by 47% of respondents as a capability that will become more important when engaging independent talent.
This expertise remains essential for organizations building, integrating or customizing AI systems. Professionals with technical AI skills can help companies select the right tools, connect AI capabilities to existing systems, and ensure implementations perform as intended.
As adoption grows, technical expertise will continue to matter—but understanding the technology is only part of the challenge. Independent professionals also need to understand the business problem AI is meant to solve and how success will be measured.
Governance, risk and compliance expertise was selected by 44% of respondents as an essential quality for the future workforce. As organizations adopt AI, they face new questions about:
How data is collected and used
Who can access it
How outputs are reviewed
How risks are managed
They also need clear policies for AI use, along with processes that meet relevant regulatory and contractual requirements.
Independent professionals with this type of experience can help organizations establish these guidelines and put appropriate safeguards in place. Their expertise enables companies to pursue AI’s benefits while managing potential legal, operational and reputational risks.
Industry knowledge turns AI output into business-ready work. In our survey, 43% of respondents selected deep domain or industry expertise as a capability they expect to become more important as AI adoption grows. Professionals with experience in healthcare, financial services or other specialized fields can assess whether AI-generated results meet customer needs and industry standards.
That expertise is equally critical to testing and training AI. Experienced professionals can identify errors and recognize missing context that some AI tools may overlook. Their input helps organizations refine outputs for specific applications and regulatory environments.
Security expertise was also selected by 43% of respondents. As AI becomes embedded in everyday workflows, organizations must protect sensitive information, manage access to AI tools and data, and understand the vulnerabilities these systems can introduce.
Professionals with expertise in data privacy, access controls and information security can assess these risks early and address weaknesses before they become larger problems. Their work helps companies adopt AI with confidence while maintaining strong safeguards for sensitive data.
The ability to test or evaluate AI outputs was selected by 30% of respondents. AI can analyze information and recommend solutions, but its outputs still need to be reviewed for accuracy, relevance and quality. They may contain factual errors or fall short of an organization’s standards.
What that review looks like varies by role:
A marketing professional may assess AI-generated content for factual accuracy and to ensure that it aligns with an organization's brand.
A data analyst may validate an AI-generated interpretation against the underlying data.
A software specialist may test AI-generated code for functionality and security vulnerabilities.
In every case, AI can accelerate the work—but professional judgment ensures the final result meets the organization’s needs.
Together, these findings suggest that organizations are looking beyond the ability to use AI itself. They also need expertise that helps them apply the technology in a business context, evaluate its results and manage the risks involved.
For independent professionals, this creates opportunities to build on existing strengths. Technical specialists may deepen their understanding of business needs, while professionals with security or compliance experience can explore how their expertise applies to AI-enabled workflows.
As AI becomes more embedded in everyday work, technical skills will remain important. But the expertise and judgment professionals bring to the technology will increasingly shape how effectively organizations use it. Independent professionals who combine these strengths will be well positioned to meet evolving client needs.
Organizations want independent professionals who can combine AI knowledge with business experience. Technical AI skills are also in demand, along with expertise in governance, risk, compliance, cybersecurity, and industry-specific knowledge. The ability to test AI outputs and assess their accuracy is another growing priority.
AI tools don't always understand the details of a specific industry. Professionals with deep industry knowledge can review AI-generated results, catch errors, and provide important context. Their experience helps organizations ensure AI outputs are accurate, relevant, and appropriate for their business needs.
Independent professionals can build AI skills while continuing to develop their existing expertise. Learning how to apply AI to business challenges, evaluate its outputs, and address security and compliance concerns can make their skills more valuable to clients as organizations expand their use of AI.