Enterprises are investing in AI technologies and tools in a rapidly evolving landscape. However, as they adopt these technologies, they realize that initiatives will fail without staff who can effectively use AI tools. While many organizations deploy AI to increase efficiency, enhance customer experience, or improve business processes, they often struggle to apply it to specific business functions.

Many companies lack the in-house expertise or formal training to effectively implement and manage AI technologies, especially complex generative AI applications. This talent shortage puts organizations at risk of falling behind their competition. According to ISG research, 56% of enterprises consider a lack of skills and expertise the biggest barrier to adopting generative AI (GenAI). AI skills have become a competitive differentiator and essential for success.

While the organization assesses its teams’ AI skills and expertise and creates a skill development strategy, it may encounter barriers that delay progress, causing it to lose valuable time and opportunities. Outsourcing AI skills can accelerate results while employees undergo training and learn to integrate AI into their roles. By partnering with an AI development company, organizations can bridge the AI skills gap and scale back external resources as they build internal capabilities for the future.

AI Skills in Demand

Incorporating generative AI into business functions requires a rapidly evolving AI skillset. Many companies report difficulties finding employees with AI-specific expertise, limiting their ability to leverage opportunities fully.

Adopting AI technologies without the necessary skills or an upskilling plan makes achieving goals challenging.

While software engineering fundamentals—such as knowledge of version control, testing, debugging, and programming in languages like Python, R, Java, and C++—are essential for building scalable and maintainable AI systems, they also serve as the foundation for advanced AI skills.

This section highlights the AI-specific skills required for a successful generative AI implementation.
Machine Learning (ML) Proficiency:

• Ability to develop and implement machine learning models.
• Knowledge of algorithms such as supervised and unsupervised learning and reinforcement learning​.
• MLOps and DevOps integration to streamline the lifecycle of machine learning models, from development to deployment, monitoring, and scaling.

Deep Learning Expertise:

• Familiarity with neural networks, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
• Hyperparameter tuning, sequence models, and transformers.
• Experience in training models using frameworks like TensorFlow and PyTorch.
• Skills in optimizing model performance and reducing computational overhead, particularly in enterprise-level deployments

Data Science and Analytics:

• Strong foundation in data manipulation, analysis, and visualization.
• Knowledge of tools like Pandas, NumPy, and Matplotlib.
• Skills in managing AI-enabled data platforms that support large-scale AI models, including vector search and retrieval-augmented generation (RAG) techniques.

Natural Language Processing (NLP):

• Understanding NLP techniques such as prompt engineering, tokenization, sentiment analysis, and language modeling.
• Familiarity with applications of generative AI, like GPT models, tailoring NLP models to specific applications (use cases).

Computer Vision:

• Ability to work with image and video processing tasks, including object detection and image segmentation.
• Experience deploying computer vision models in real-time applications, particularly for business process optimization.

Model Fine-Tuning and Optimization:

• Experience in fine-tuning pre-trained models for specific tasks.
• Customizing AI solutions to fit unique enterprise environments, including iterative development and system integration
• Ability to optimize model performance while reducing computational overhead​.

Cloud Computing and AI Deployment:

• Proficiency in deploying AI solutions on cloud platforms like AWS, Azure, or Google Cloud. Cloud architecture and the ability to adapt, monitor, and troubleshoot cloud solutions.
• Knowledge of containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable AI deployment.
• LLMOps expertise in managing large language models (LLMs) in production environments, focusing on monitoring performance, updating models, and ensuring scalability.
• Managing AI-ready infrastructure, including decisions about on-premise vs. public cloud hosting and knowledge of AI accelerators like GPUs​.

AI Ethics and Governance:

• Understanding AI governance frameworks, including ethical considerations in AI, risk management, and compliance with global AI regulations.
• Understanding of ethical considerations in AI, including bias detection, fairness, and responsible AI use​.

Automation and AI-Driven IT Operations (AIOps)

• Expertise in AIOps, using AI to automate and optimize IT operations, including incident response, predictive maintenance, and resource management.
• Ability to integrate AI-driven tools to improve operational efficiency and reduce manual oversight.

Communication and Collaboration:

• Ability to effectively communicate complex AI concepts to non-technical stakeholders.
• Experience collaborating across multidisciplinary teams.

AI Product Management:

• Skills in managing AI projects from concept to deployment.
• Proficiency in aligning AI initiatives with business goals and driving ROI from AI investments​.
• Familiarity with sequencing AI projects for long-term business impact and strategic value.

Krasamo’s AI Skills Offering

Krasamo offers AI development services tailored to your organization’s needs and infrastructure. Our team provides the expertise to develop custom solutions based on your data and systems, helping address internal skill shortages with specialized AI knowledge. Whether through direct collaboration with our experts or by leveraging contractors and staff augmentation, we ensure that your AI initiatives have the right talent in place.

Partner with us to create POCs that test AI solutions in your environment while optimizing them for scalability and robustness. Your developers can participate in these projects, gaining hands-on experience and building expertise in AI technologies alongside our specialists. By working with Krasamo, you reduce the risk of investing resources in inefficient projects and gain access to expertise, along with advanced tools, frameworks, and technologies that may not be readily available in-house.

AI Skills as Strategy

As AI skills are crucial for immediate implementation, organizations must align their talent development with long-term AI strategies. A comprehensive Generative AI Strategy can help businesses integrate these skills into a roadmap for sustainable growth and intelligent transformation.