How to Put the Right Skills in Place to Enable GenAI Adoption.

Adopting GenAI is not without its challenges. As many organisations are discovering, the journey to effectively implement and leverage GenAI requires careful planning, especially around the right skills and resources. 

Here’s what we’re hearing from clients:

“Big ideas, lots of drivers, not enough people.”

“Difficulty in finding skilled professionals who can manage and implement Generative AI.”

“Difficult keeping up with rapid advancements in AI technology and applying them effectively.”

“Difficult supporting the user adoption and change management.”

“Understanding our Gen AI use cases and what can be done.”

“Rolling out Generative AI tools is challenging due to skill gaps in AI expertise.”

So, how can organisations overcome these hurdles and successfully put the right puzzle pieces in place to adopt Gen AI? 

The Importance of a Multi-Disciplinary Team

Building successful AI solutions requires a diverse range of skills. From data scientists and machine learning engineers to UX designers and product managers, the talent pool needed is vast and varied. And finding the right talent in a competitive market can be a significant challenge.

A well-rounded AI team should include, as a priority:

Data Scientists: To analyse and interpret complex data.

Machine Learning Engineers: To develop and deploy machine learning models.

UX Designers: To ensure that AI solutions are user-friendly.

Product Managers: To oversee the development and lifecycle of AI products, and align them with the business.

There are a variety of other roles that can help ensure the delivery of a successful AI implementation:

The Path to AI-Powered Transformation: A Marathon, Not a Sprint

Adopting Gen AI is a long-term endeavour that requires patience and perseverance. It's important to adapt and learn continuously, acknowledging the challenges and proactively seeking solutions. Remember, all your competitors are facing similar obstacles, so turning these challenges into opportunities can give you a competitive edge.

Hire the A(I)-Team Instead of Building In-House

Building and maintaining an in-house AI team is challenging and expensive. Instead, consider hiring flexible, scalable teams packed with specialist skills that can start delivering for you immediately. 

This approach allows you to bypass acute resource constraints and accelerate your AI development pipeline. It is the most cost-effective and efficient way to build a diverse range of AI solutions without the burden of hiring and managing a large in-house team.

Build a Solid Foundation by Training Your Staff

Gen AI is still a relatively new field. To effectively use the technology and understand its capabilities, it’s crucial to quickly build an adequate technical understanding throughout your business. Investing in Gen AI training can be incredibly beneficial.

There are comprehensive training programs available that cover everything from the basics of AI and machine learning to more advanced concepts like natural language processing and generative models. These programs help your teams develop the knowledge and skills they need to confidently bring your AI ambitions to life.

At Nordcloud, our Gen AI training programs cover both theoretical foundations and practical applications. By participating, your teams will gain the expertise needed to drive your AI initiatives forward.

Checklist: What You Need to Put in Place for Your People

To ensure your team is ready for GenAI, consider the following:

Training

• User Training: Educate end-users on how to effectively interact with AI tools.
• Technical Development & Maintenance: Provide ongoing training for technical staff to stay current with AI advancements.
• AI Academy: Establish an internal academy to foster continuous learning and development.

User Experience

• UX Service Design: Focus on creating intuitive AI interfaces.
• UI Development: Ensure seamless user interactions.
• Change Management & Communications: Facilitate smooth transitions and keep stakeholders informed.

Observability & Monitoring

• Usage Tracking: Monitor how AI tools are being used to ensure they meet user needs.
• Feedback Gathering: Collect and act on user feedback to improve AI solutions.
• Application Insights: Gain insights into AI application performance and impact.

By putting the right skills and resources in place, organisations can overcome the challenges of GenAI adoption and harness its full potential. With a strategic approach and a commitment to continuous learning, the path to AI-powered transformation can be navigated successfully.

What Resources Do We Need to Succeed?

Beyond personnel, adopting GenAI requires specialised tools, infrastructure, and data resources. It can be difficult to assess where the gaps are in this new area, but understanding your needs is crucial for success.

Specialised Tools and Infrastructure

To support Gen AI adoption, consider investing in:

AI Development Platforms: Tools that provide a suite of AI capabilities.

High-Performance Computing Resources: Necessary for training complex AI models.

Data Management Systems: To store and manage large datasets efficiently.

Data Resources: High-quality data is the backbone of any AI initiative. Ensure you have access to relevant, clean, and well-organised data to train your AI models.

Example: What if you don’t get it right?

Company X attempted to implement a GenAI-powered chatbot for customer support, without the right specialist AI skills in-house. 

The existing IT team, lacking expertise in AI model development, data management, and user experience design, struggled with the project. They used poor-quality data for training, resulting in a chatbot that frequently misunderstood customer queries. 

Additionally, without proper change management and user training, both customers and employees found the chatbot difficult to use. 

The absence of monitoring tools meant issues went unresolved, leading to low user adoption and growing customer dissatisfaction. Ultimately, the project failed, costing Company X significant resources and damaging its reputation.

Example: What if you get it right?

Company Y successfully implemented a GenAI-powered chatbot for customer support by working closely with a team of outsourced AI specialists. 

The team included Data Scientists, Machine Learning Engineers, and UX Designers to ensure robust AI model development, high-quality data management, and a user-friendly interface. 

The project was guided by experienced Project Managers and supported by Change Management Specialists who facilitated smooth user adoption and effective communication. The team used clean, well-preprocessed data for training, resulting in an accurate and reliable chatbot. 

Continuous monitoring and feedback mechanisms were put in place to track performance and address issues promptly. Employees received thorough training, and customers found the chatbot intuitive and efficient. 

The successful deployment enhanced customer satisfaction, reduced the workload on human agents, and positioned Company Y as a leader in AI-driven customer service, showcasing the importance of the right skills and resources for GenAI adoption.