AI developer certifications tech companies want

Cloud computing and cybersecurity are among the featured players on the contemporary software development stage, but artificial intelligence (AI) is the star. AI continues to gain momentum as a force for business growth and opportunity, and tech and business leaders are looking to development teams to churn out products that leverage its capabilities.

Naturally, there is a rising demand for certifications focused on AI-related skills.

“We’re seeing a massive uptick in candidates listing AI certifications on resumes, primarily driven by companies embedding AI tools into mainstream software development workflows,” says Steve Taplin, CEO at Sonatafy Technology, a cloud and mobile application software development company. “Developers want to demonstrate that they can build with AI, not just use it.”

Pervasive AI adoption, the emergence of new roles in AI, rapidly evolving AI technology, and competitive career pressure are driving credentialing for AI developers, says Matt Scicchitano, manager of the Global Certification program at software company SAS.

“Because AI is so new and changing so rapidly, developers see earning certifications and other credential types as a way to focus their learning and prove skills where hands-on experience may be limited and traditional degree programs do not exist or are trying to catch up to market required skills,” Scicchitano says.

Enterprises facing pressure to adopt AI, especially generative AI, “see certifications as a hedge against talent gaps and operational risk,” says Dion Hinchcliffe, vice president and practice lead, Digital Leadership & CIO at the Futurum Group, a global technology research and advisory firm.

Certifications help ensure developers understand AI governance, security, and responsible use, Hinchcliffe says. Certifications from vendors such as Microsoft and Google, along with OpenAI partner programs, are driving uptake, he says. “Strategic CIOs see certifications less as long-term guarantees of expertise and more as a short-term control and competency mechanism during rapid change,” he says.

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The importance of AI certification in hiring

With the current technology talent shortage in AI, “a certification can be a ‘tie-breaker’ that makes a candidate stand out,” Scicchitano says. “A factor unique to AI—because it is so new and hands-on experience is still scarce for many—certifications offer third-party validation of a candidate’s skills.”

AI certification can accelerate the interview process by giving hiring managers and recruiters confidence the person has baseline competencies, so they can focus interview time on deeper problem solving or culture fit, Scicchitano says.

While certifications aren’t the sole deciding factor in landing a job, they often help candidates stand out in competitive roles where AI literacy is becoming a crucial factor, Taplin says. “This is especially true for new software engineers, who can gain a leg up by focusing on certifications early to enhance their career prospects,” he says.

Smart developers are treating AI certifications like “career insurance policies,” says Brady Lewis, senior director of AI innovation at Marketri, a strategic marketing consulting firm. “In my 20 years in tech, I’ve never seen a technology shift this fast, where the choice is literally, adapt or become obsolete. [Developers] getting certified now aren’t just adding skills, they’re securing their relevance in a post-AI world.”

Hiring managers are telling Lewis they’re overloaded with resumes from developers “claiming AI expertise based on weekend ChatGPT experiments,” he says. “Certifications cut through that noise instantly.”

The importance of AI certifications for developers depends on the hiring manager, says Mark Runyon, fractional CTO at Honest Jobs, a company that helps businesses hire formerly incarcerated job seekers.

“The AI engineering space is so new and changing so quickly that getting a stamp of approval on your skills can be a fleeting validation,” Runyon says. “I want to know what steps you are taking to handle how AI is shifting and changing today. How are you employing a growth mindset to flourish in this space?”

As with other software development certifications, a mix of experience and certificates is ideal. “[Certifications] are not a substitute for experience but serve as a ‘signal’ of baseline competency in an AI stack or platform,” Hinchcliffe says. “In high-stakes enterprise contexts, such as financial services, healthcare, or regulated industries, hiring managers value certified candidates to mitigate risk.”

The advantage of certifications is greatest where proprietary ecosystems such as Microsoft Azure, Amazon Web Services (AWS), and Amazon’s SageMaker machine learning service dominate, Hinchcliffe says. For leading-edge AI research and development, certifications hold less weight compared with demonstrable project portfolios and open source contributions, he says.

AI certification is only one part of hiring evaluation

Some see AI certifications as less important in the hiring process.

“The real demand is for AI skills, and certifications are simply one way to build those skills in a structured manner,” says Kyle Elliott, technology career coach and hiring expert.

“Hiring managers are not necessarily looking for candidates with AI certifications,” Elliott says. “However, an AI certification, especially if completed in the last year or currently in progress, can signal to a hiring manager that you are well-versed in the latest AI trends. In other words, it’s a quick way to show that you speak the language of AI.”

Software developers should not expect AI certifications to be a “silver bullet for landing a job or earning a promotion,” Elliott says. “If you are not qualified for a role, a certification alone will not change that. That said, if you already meet the qualifications and want to stand out from other applicants or colleagues, an AI certification can help set you apart.”

“It’s not about the certificate. It’s about whether you can actually build,” says Wyatt Mayham, CEO and cofounder at Northwest AI Consulting. “No CTO is out here saying, ‘we need someone with an AI cert.’ They’re saying, ‘we need someone who can help us ship faster, smarter software.’ Certifications are just the side-effect of everyone scrambling to catch up.”

Early-career developers should understand that an AI certification might get their resume noticed, but it won’t carry them through interviews. “Show me how you’ve used AI to solve something real,” says Mayham.

The benefits of AI certification

Like other certifications, those focused on AI-related skills can deliver benefits for both individuals and organizations.

For individuals, “I see AI certifications as a great way to round out your skills in the AI space,” Runyon says. “Preparing for AI certifications can be a great study guide and primer of the wider world of AI tools, to help you understand what is possible.”

AI certifications “demonstrate your commitment to learning and staying current,” Elliott says. “They also provide structured opportunities to keep up with AI trends and connect with professionals beyond your company who may open doors to new opportunities. Many of my tech clients find these programs valuable for creating a dedicated space for networking, which often gets neglected once you are established in a role.”

Most people don’t finish a certification program “because they want the badge,” Mayham says. “They do it because it gives them a clear learning path. The AI ecosystem is chaotic and fast-moving, so having a framework to follow is useful.”

Certified AI specialists can earn more than their non-certified peers, “and hiring managers are specifically screening for them because they represent candidates who’ve invested serious time and effort into structured learning rather than just following YouTube tutorials,” Lewis says.

“AI certifications are insurance against technological obsolescence,” Lewis says. “They provide structured learning paths through rapidly evolving technology landscapes and demonstrate commitment to continuous learning. More importantly, they position you to capitalize on AI market expansion rather than being displaced by it.”

For enterprises, AI certifications can provide enhanced operational trust with AI projects. “Certifications assure CIOs that teams can deploy AI within governance frameworks,” Hinchcliffe says. For example, Microsoft’s certifications include security and compliance modules.

Certifications can also lead to faster adoption of solutions. Certified staff can accelerate the rollout of AI platforms by reducing learning curves, Hinchcliffe says.

In addition, AI certifications can increase organizational readiness, Hinchcliffe says. “Certifications can help standardize practices across IT teams, critical for scaling AI responsibly,” he says. For instance, a bank deploying generative AI chatbots might require Azure AI certifications for all developers working on its conversational layer, to align with governance policies.

“Strategic CIOs see certifications less as long-term guarantees of expertise and more as a short-term control and competency mechanism during rapid change,” Hinchcliffe says.

Certifications can speed up onboarding and help teams adopt AI-driven processes faster, Taplin says. “For example, a developer certified in integrating AI-assisted code generation tools can immediately help us improve sprint velocity.”

Popular AI certifications

The following certifications are currently popular with developers and tech leaders.

AWS Machine Learning Specialty

This certification ensures developers are familiar with deploying machine learning solutions in the Amazon Web Services cloud. Certificate holders have demonstrated they know how to implement streaming and advanced projects, solve classic regression and classification problems, use AWS machine learning services for predictive analytics, and leverage the AWS ecosystem to access extended data sources. Learning providers include Udemy and Whizlabs.

Google Professional Machine Learning Engineer

This certification attests to a candidate’s ability to architect low-code AI solutions, collaborate within and across teams to manage data and models, scale prototypes into machine learning models, and automate and orchestrate machine learning pipelines, among other skills.

IBM AI Engineering Professional Certificate

Those pursuing this certificate learn to implement supervised and unsupervised machine learning models, deploy machine learning algorithms and pipelines, and build deep learning models and neural networks.

Microsoft Azure AI Engineer Associate

This certificate ensures holders can design and implement Azure AI solutions using Azure AI services, Azure AI Search, and Azure OpenAI. Ideal for teams already leveraging the Microsoft ecosystem.

NVIDIA NCA Generative AI LLMs

An entry-level credential that validates the foundational concepts for developing, integrating, and maintaining AI-driven applications using generative AI and large language models (LLMs) with NVIDIA solutions.