By Bill McCabe

Predictions Across IoT and Artificial Intelligence Jobs – 2024

As we have entered 2024, the transformative power of AI and IoT on society and technology is absolute. 

These innovations reshape businesses, entire industries, and even the job market. As companies rush to integrate AI and IoT capabilities, new roles emerge while existing jobs evolve.

Nvidia’s Strategic Shift Towards Cloud Services

Nvidia has pivoted from primarily a graphics chip provider into offering a suite of AI and cloud computing services. 

This includes its Omniverse platform for 3D simulation and collaboration and specialized cloud solutions optimized for machine learning.

Industry experts predict this move will accelerate AI adoption and make it more accessible. Small and medium businesses can now leverage Nvidia’s infrastructure instead of building their own. 

This democratization of AI will create new data science and ML engineering jobs tailored to business needs.

At the same time, Nvidia’s pivot puts it in direct competition with established cloud providers like Amazon Web Services (AWS) and Microsoft Azure. 

It may emphasize vertical-specific AI services, making roles like “Manufacturing AI Specialist” or “Healthcare AI Consultant” stand out.

The Turbulent Journey and Predicted Demise of Stability AI

Stability AI made waves in 2023 with its stable diffusion text-to-image generator. However, it has since faced backlash over copyright concerns, model bias, and accessing private code repositories without consent.

Experts believe Stability AI expanded too fast without establishing strong foundations around ethics and security. Unless it can rebuild user trust, it may struggle to survive until 2024.

These developments underscore the challenges faced by AI startups. Striking the right balance between rapid prototyping and robust systems design is now a competitive necessity. 

Only startups that incorporate ethical AI practices will attract the talent or funding they need.

Consequently, demand is rising for AI professionals skilled in domains like ethics, auditing, and governance instead of just technical capabilities. 

Job roles like “Responsible AI Lead” and “Algorithmic Bias Auditor” will likely see increased recruitment activity.

The Evolution of AI Terminology and Its Impact on Job Roles

What was once broadly encompassed by the term “large language model,” AI now consists of diverse architectures like memories, reasoners, and reinforcement learning systems. 

This evolution seeks to overcome reasoning, interpretability, and knowledge retrieval limitations.

As AI capabilities expand, job roles are shifting, too. Demand for “Conversational AI Designer” and “Intelligent Agent Architect” positions highlights the industry’s focus beyond language generation. 

Recruiters also prefer candidates with cross-disciplinary exposure spanning computer science, neuroscience, cognitive psychology, and linguistics.

The Debate of Open vs. Closed AI Models: Future Implications

An ideological debate has erupted around developing open-source versus proprietary AI systems and huge language models. Advocates of open AI argue that transparency and accessibility lead to more robust innovation within ethical bounds. 

Conversely, big tech firms counter that only closed models align commercial incentives to guide cutting-edge research responsibly.

Industry observers expect hybrid approaches blending open and closed protocols to dominate eventually. 

This implies consolidated power with a handful of Big Tech companies that can afford significant investments in AI — potentially hurting smaller firms and startups. Consequently, jobs may shift towards implementing and customizing licensed AI platforms rather than fundamental research or building new systems from scratch.

The Rise of Chief AI Officers in Corporate Strategy

Many companies now boast a Chief AI Officer (CAIO), reflecting AI’s prominence in strategic decisions. 

The CAIO formulates policies around data analytics, intelligent workflows, AI ethics, and emerging technologies. Moreover, they identify AI applications that align with broader business goals to drive digital transformation.

The popularity of CAIOs indicates that “AI Strategist” will emerge as an essential job category. 

These in-house consultants will audit current processes, propose AI adoption roadmaps, liaise between departments, and measure results — serving as force multipliers for company-wide AI effectiveness.

Emerging AI Architectures: Beyond the Transformer Model

The transformer architecture has been fundamental to breakthroughs like OpenAI’s GPT models and Google’s PaLM system. 

However, newer paradigms are now challenging its supremacy. This includes graph neural networks like Anthropic’s Constitutional or limit-based approaches exemplified by

As novel AI architectures gain prominence, they will require reinventing job roles. Graph neural networks leverage knowledge representations closer to symbolic reasoning. 

This reduces reliance on huge annotated datasets. Consequently, roles like “Knowledge Engineering Specialist” and “Ontology Architect” may witness surging demand in coming years.


Q: Which industries will see the biggest job growth in AI and IoT?

A: Autonomous vehicles, smart cities, manufacturing, healthcare, and finance are expected to generate the most new AI and IoT jobs by integrating these technologies into core operations.

Q: What are some rising AI job profiles for technical professionals?

A: Machine learning engineer, AI solutions architect, robotics designer, neural network developer, trust & safety specialist, generative media producer, and simulation engineer are increasingly common and lucrative roles.

Q: Are certifications necessary to be employable in AI?

A: While degrees in computer science or related quantitative fields will be preferred, domain-specific AI certifications in tools like TensorFlow, PyTorch, and ONNX from providers like IBM and Microsoft are valuable additions to boost employability.


AI and IoT will keep advancing beyond 2024, bringing their transformations. We expect continued demand for engineering talent as emerging applications permeate consumer tech and industrial infrastructure. 

However, the associated social implications also underscore the growing importance of cross-disciplinary skills around ethics, governance, user privacy, and human-AI collaboration. 

Companies that keep these holistic considerations in mind will likely attract the best candidates for the jobs of tomorrow.

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