AI hiring now extends to integration and security

AI hiring now reaches beyond AI-tool proficiency

An artificial intelligence (AI) hiring plan needs to cover the work that makes tools usable inside an organization: connecting them to enterprise data, securing their use, governing decisions, and managing costs. Dice’s September and July 2026 Jobs Reports show employers seeking these capabilities alongside strong demand for AI tools. Dice has a commercial interest in technology recruitment because its hiring business benefits from employers seeking technology workers. Its findings describe the widening range of expertise needed to put AI to work across an organization.

The requirements grow as employees use AI tools and organizations move ahead with implementation. Wider use brings security threats, governance requirements, ethical questions, and operating costs that need oversight. Dice describes employers responding by paying more hiring attention to security, finance, and related capabilities. Tool proficiency remains central, but employers also need people who can put those tools into operation and manage their use.

Strong tool demand creates a wider implementation workload

The scale of hiring demand helps explain why implementation deserves attention. In the Dice September 2026 Jobs Report, information technology (IT) job postings rose 17% year over year compared with September 2025. Postings increased through September after a slight dip in August, while postings involving artificial intelligence and machine learning grew 88% compared with 2025, about five times faster than average technology-posting growth. Machine learning uses systems that learn patterns from data to make predictions or perform tasks.

AI requirements also appeared across a large share of technology openings. The Dice July 2026 Jobs Report put the share of US technology openings requiring AI fluency in June at 75%, up 178% year over year. AI fluency means understanding and working with AI in the context of a job, whether in an established technical occupation or a dedicated AI role. Such a widespread requirement puts workers who lack it at a substantial hiring disadvantage.

Within that broad demand, specific tools continued to attract employers. Dice’s September annual skill-growth list was led by Claude AI at 1033%, and Dice also highlighted agentic AI, meaning systems that can take actions through a sequence of tasks. These findings give employers reason to keep tool expertise in hiring plans while examining the work needed to deploy those tools. Recruitment for implementation skills runs alongside demand for the tools themselves.

The reports’ timing helps separate sustained demand from recent movement. Dice reported increases in AI-skill demand both year over year and month over month, with September’s emphasis resembling the earlier June data. Annual growth measures change over a longer interval, while monthly growth captures more recent movement. Recruitment planning needs to keep those views distinct.

Integration connects AI adoption to enterprise work

Enterprise integration makes that implementation demand concrete: it means getting separate applications, data sources, and processes to work together. An agentic system needs connections to the infrastructure employees use to find information and complete work. Those connections must meet the organization’s technical and operating requirements, so employers need people who can connect AI systems to existing enterprise operations.

Dice’s July report placed enterprise integration first for annual skill-demand growth, with a 638% increase from June 2025 to 2026. Dice described the pattern this way: “connecting agentic systems to existing infrastructure is growing faster than the agentic systems themselves.” Its September report again included enterprise integration among the fastest-growing annual skills, at 376%. Its presence in both reports shows recurring demand, though each percentage describes its own reporting period.

Dice’s July monthly figures show what some of that connection work involves. API system integration rose 58%; an application programming interface, or API, defines how software systems communicate. Data exchange increased 53%, and enterprise integration rose 50%. Dice linked demand for these skills to efforts to “connect AI systems to enterprise data and workflows,” tying the hiring pattern to the work needed to make AI useful within an organization.

Those connections also require identity controls and security expertise. July’s monthly list included LDAP, a protocol for accessing directory information, and SAML, a standard for exchanging identity and authentication information. It also included digital forensics, which involves examining digital evidence; threat detection, which involves identifying potential attacks; and the NIST Cybersecurity Framework, which organizes cybersecurity risk-management practices. These skills put the integration findings in a security context, although their growth covers work beyond AI adoption.

Dice’s September report added a more recent security signal through endpoint detection and prevention, the work of identifying and stopping threats on devices such as employee computers. Demand for that skill grew 51% month over month. Dice linked the increase to emerging risks from AI implementation and described companies further along in adoption as prioritizing cybersecurity and governance. Governance assigns responsibility for decisions and oversight, giving organizations a way to manage how AI is used.

Responsible AI adds judgments about acceptable use to those technical controls. The term covers practices intended to make AI use accountable and ethically appropriate, and Dice reported that demand grew 401% annually in September. Annual growth in both reports indicates employer interest in responsible deployment alongside implementation. People with this expertise help turn oversight requirements into decisions about how teams may use AI.

Costs create another responsibility as implementation expands. Dice’s September monthly list included FinTech, meaning financial technology, at 43%, which Dice associated with managing the costs of AI processes and tools. Dice also identified financial operations supporting AI costs among the priorities of companies further along in adoption. The hiring figure measures demand for a skill associated with that concern; AI operating expenditure is a separate measure.

The skill inventories span several kinds of work

Integration, security, and cost management sit within a broader technical hiring market. Dice reported that electronic engineering remained the fastest-growing monthly skill since July, reaching 64% in September, while demand for skills used to manage AI systems also increased during September. Database management systems support the storage and maintenance of information, and data migration moves information between systems. Autodesk Revit appears in the same mixed technical market as a building-design software skill, so the monthly list covers a wider range of work than AI implementation.

The annual lists likewise span several technical layers. AI infrastructure covers the computing systems and supporting services used to develop and run AI, while vector databases store representations used to retrieve related information. Event-driven programming organizes software behavior around events, and prompt engineering concerns how requests to AI systems are formulated. Observability means understanding system behavior through its outputs and operating data. Product family engineering develops related products from shared foundations.

Other entries describe the practices and capabilities needed to carry out that work. Tooling covers the tools used in development and operation, engineering practices concern how technical work is performed, and AI adoption concerns bringing AI into use. AI agents are systems that carry out tasks. Creative problem solving, team performance management, and demonstration skills concern how people solve problems, coordinate work, and explain results. Together, these categories show the range of demand without assigning every skill to the same implementation need.

The complete inventories below keep each report’s comparison period. Every percentage measures growth in demand for the named skill, rather than its share of all openings. A fast-growing skill can still account for fewer vacancies than an established one, so these figures help identify capabilities to examine without determining how many people a team needs.

Existing technical roles carry the changing skill mix

These capabilities matter to workforce planning because employers continue to seek familiar technical occupations. Dice names software engineers, data engineers, systems engineers, electrical engineers, and business analysts among the most sought-after roles. Its list also includes data scientists, network engineers, systems administrators, data analysts, and AI engineers. Dedicated AI positions sit within a hiring market that still depends on established engineering, infrastructure, and analysis functions.

Demand for those functions extends across industries. In the July report, consulting led the industries seeking IT workers, followed by software, with aerospace/defense, finance/banking, and manufacturing completing the top five. Dice describes employers pursuing enterprise AI tools and services as increasingly seeking AI and related capabilities within occupations already in demand. A familiar title can therefore carry new requirements as an employer’s implementation plans develop.

Enterprise application and consulting roles show where some of those responsibilities already sit. Employers are seeking enterprise systems and consulting managers, with role descriptions including Appian developers, Oracle Cloud financial consultants, ServiceNow managers, principal consultants, and technology consultants. Appian, Oracle Cloud, and ServiceNow identify technologies within those descriptions. Their appearance connects hiring demand to enterprise application and consulting work; they are examples of requested expertise rather than accounts of implementations by those vendors.

Engineering and support roles extend that work into building, operating, and protecting systems. Dice also identifies demand for IT software engineers, C++ software developers, configuration analysts, support engineers, and network infrastructure engineers, alongside AI analysts and cyber threat intelligence analysts. Employers can assign implementation responsibilities within these existing occupations. The question is which responsibilities fit each role’s work.

Security and finance make the organizational implications particularly clear. Dice describes AI implementation as bringing security, governance, ethical-use, and financial challenges, with employers responding by paying more hiring attention to security and finance. Its reported demand for endpoint detection and prevention, Responsible AI, enterprise integration, and financial technology illustrates that response. Hiring plans need to identify who will oversee use, manage emerging threats, and track spending as tools become part of routine operations.

Human capabilities support those responsibilities too. Alongside the monthly entries for creative problem solving, team performance management, and demonstration skills, Dice’s broader discussion identifies critical thinking as a hiring priority. These capabilities help people evaluate problems, coordinate teams, and explain how systems work. Their value extends across technical work, including the decisions and collaboration that implementation requires.

Dice expects employers inside and outside technology to keep seeking workers who can carry out their AI plans, requiring a broad range of AI fluency and skills. It places that expectation in a labor market recovering gradually after several tumultuous years and anticipates continued demand for the foreseeable future. For workforce planning, this means assessing AI capability across teams responsible for implementation and ongoing operation. Posting growth describes employer requirements, while completed hires and business outcomes are different measures.

A practical assessment begins by assigning each implementation responsibility to an existing or proposed role. A role connecting AI to enterprise workflows needs explicit integration requirements; a role overseeing use needs clear governance and security responsibilities. Where one position combines several duties, its description should explain that combination so candidates and hiring managers can distinguish the expertise required. Responsibility for AI spending also needs an identifiable place in the staffing plan.

Engineers can use those role requirements to choose which capabilities to develop. Tool fluency remains valuable, and recurring demand for integration, security, and responsible use offers additional areas to assess against their current work. The choice depends on the responsibilities they want to take on. Growth in postings signals employer interest without promising employment to someone with a particular combination of skills.

Local hiring conditions qualify the national picture

The responsibilities may be widespread, but opportunities vary by location. Dice’s metropolitan figures show that between June and September, Washington moved ahead of New York, while New York fell from over 20,000 postings to just over 16,000. The metropolitan figures below show advertised IT opportunities at those two points. They measure posting volumes, so they need a different reading from annual growth rates.

Every listed metropolitan area had fewer postings in September than in June. Dice nevertheless describes Dallas, Chicago, and San Francisco as relatively unchanged over that period and as showing potential hiring stability. Washington also moved into first place while its own count declined. Ranking describes a market’s position against other markets, so a higher rank can accompany a lower posting total.

The earlier July discussion had identified New York, Washington, Dallas, Chicago, and San Francisco as having stronger posting growth than the rest of the country. Their prominence as hiring locations can coexist with the later June-to-September declines because the comparisons cover different periods. The national increase compares September with the same month a year earlier. The metropolitan table instead tracks change from June to September.

State growth adds another measure of local conditions. Dice’s July discussion identifies New Jersey, at 64%, Maryland, at 47%, and Illinois, at 41%, as the states with the highest year-over-year hiring increases. Those percentages measure change across state markets, while the metropolitan counts describe the volume of openings in individual urban areas. Hiring managers choosing where to recruit, and candidates choosing where to search, need to distinguish a market’s size from how quickly it is growing.

Key executive takeaways

• Plan for broad AI fluency: Dice reported 88% annual growth in AI and machine learning postings in September 2026. Hiring managers need to define the AI capabilities required within each role as demand spreads across established technical occupations.
• Assign implementation ownership: Integration, security, responsible use, and cost management create distinct staffing responsibilities. CTOs need clear owners for connecting AI to enterprise workflows, managing risks, and tracking spending.
• Use skill-growth figures carefully: Rapid growth signals employer interest, while vacancy volume determines the scale of hiring demand. Workforce planners need both measures before setting recruitment priorities.
• Update established technical roles: Software engineers, systems administrators, analysts, and enterprise consultants increasingly carry AI implementation responsibilities. Hiring managers need job descriptions that specify which integration, oversight, and operating duties each position includes.
• Match recruitment to local conditions: All five listed metropolitan markets recorded fewer IT postings in September than in June, despite national year-over-year growth. Recruitment teams need local posting volumes and comparable growth periods when choosing where to hire.