The digital landscape is on the cusp of a major transformation – the integration of Artificial Intelligence (AI) into core design and development processes. Here at Loomery we understand the potential for AI to streamline workflows and revolutionise user experiences. 

The changes organisations need to make depend on their technical maturity, and the use cases they plan to pursue, but in general fall into two camps. First, entirely new skills will be needed, and  the roles people play when developing digital experiences with AI will change. Second, ways of working, mindsets and approaches across all digital development will be redefined by the AI era. 

In this post we’ll explore both, to help you prepare your team for success in the AI era.

The evolving landscape of digital design and development

The new skills needed will of course vary by discipline. Let’s consider the core roles in a typical product team today. 

Changes by role:

Designers:

• New interfaces and interaction methods: AI assistants, co-pilots, and other intelligent systems will necessitate a focus on designing for dynamic interactions. Designers will need to consider user inputs that guide AI-powered features and how to test experiences tailored to individual users.
• Infinite canvas, finite control: As AI enables more flexible interfaces, designers will grapple with maintaining brand consistency within an ever-evolving environment.
• The rise of prototyping for adaptability: With AI personalising experiences, traditional prototyping methods might need to adapt to test for a wider range of user interactions and outcomes.

Engineers:

• Data and ML literacy: Working with AI platforms demands familiarity with data science and Machine Learning (ML) principles. Engineers will need to understand how data informs AI models and leverage new tools like co-pilots for development.
• Prompt engineering: Constructing clear and concise prompts for AI tools will be a crucial skill for some engineers. This involves communicating desired outputs and guiding AI models with specific instructions.
• Shifting focus: The rise of Large Language Models (LLMs) that can automate some coding tasks may lead to a shift in engineers' responsibilities. They might focus more on product architecture, testing, and acting as product managers, while LLMs handle the heavy lifting of code generation.

Product managers:

• Automation vs. Control: Product managers will need to strike a balance between automation and human control. AI can personalise experiences to a great extent, but human oversight remains crucial for strategic decision-making.
• Conversational interfaces: The prevalence of conversational interfaces (e.g. chatbots) necessitates a new set of accessibility considerations. Product managers will need to ensure these interfaces are inclusive and user-friendly.‍
• Data-driven strategies: AI thrives on data. Product managers must identify and leverage relevant data sets to enhance AI models and deliver exceptional customer experiences. Measuring the success of highly personalised experiences will also be a new challenge.

Beyond roles: Embracing the AI shift

While these changes impact specific roles, fostering a team culture that embraces AI is equally important. Here are some key areas to consider:

• Tool adoption: To leverage AI effectively, teams must adopt tools that allow them to work faster and smarter. This includes everything from AI-enhanced design software to code co-pilots, to advanced data analytics platforms. The integration of these tools requires a nimble approach to project management and development.
• Experimental mindsets: An experimental mindset will be crucial. Teams must be willing to adapt their methods continuously and embrace the iterative nature of AI-driven development. This means being open to failures and learning from them quickly, which is essential for innovation in a rapidly evolving tech landscape.
• Ethical considerations: As AI technologies become more integral to product development, the importance of moral and ethical decision-making grows. Teams must navigate the complexities of AI ethics, from data privacy to the broader societal impacts of their products. Developing a framework for ethical AI use within the organisation is not just beneficial but necessary.
  

Conclusion: Preparing for success

The transition to AI-driven development isn't just about adopting new technologies; it's about evolving every aspect of how teams operate. It requires comprehensive changes in skills, roles, and mindsets, and the time to start is now.

For companies willing to make these changes, the rewards are substantial: increased efficiency, more innovative products, and a stronger competitive position in the digital marketplace. As we continue to explore the impact of AI on various facets of business, staying adaptable and informed will be key to success.

Stay tuned for more insights in our series as we delve deeper into specific strategies for integrating AI into your business practices or get in touch to learn how Loomery can help you prepare.