Run hackathons and innovation challenges to build AI literacy

Artificial Intelligence (AI) is no longer a futuristic concept reserved for science fiction; it’s now transforming industries, enhancing productivity, and redefining how we approach problem-solving and innovation. As AI becomes increasingly accessible for all employees, its ability to augment human intelligence offers unparalleled opportunities for every organisation. If you can prompt, you’re already one step ahead. However, to harness AI effectively, users have to understand the problems they are trying to solve. Once you understand the problem, AI becomes an invaluable tool, offering solutions that are faster, more efficient, and often more innovative than traditional methods.

First, define the problem

Before diving into AI, it's crucial for users to have a clear understanding of the problem at hand. AI's power is in its ability to process vast amounts of data, identify patterns, and suggest solutions. However, without a well-defined problem, AI's capabilities can be underutilised or misdirected. For instance, deploying AI in customer service to automate responses can only be effective if the business understands the common issues customers face and how AI can address them. You first have to define what the problem is and have a deep understanding of it because that will be the foundation upon which successful AI implementation is built.

Focus on key areas for AI literacy

To fully leverage AI, workplace AI literacy is essential. Over the past year many organisations have acknowledged they need to upskill their employees but running one-time AI literacy training courses or elearning barely scratches the surface. Prompt engineering skills are very useful for any employee but just training how to prompt is limiting. It’s at the strategic level, knowing the problems and opportunities, the areas of conflict and growth, efficiencies to be gained, the full competitive landscape, regulatory risks and talent impact/opportunity that AI literacy shines. It’s a whole lot more than just understanding what AI is; it involves knowing how AI works, its limitations, and its potential applications.

1. Data Management and Analysis
Data is the lifeblood of AI. However, many organisations struggle with managing and analysing the vast amounts of data they collect. AI literacy enables employees to understand the importance of data quality, how to clean and prepare data for AI models, and how to interpret the results. This knowledge ensures that AI tools can provide accurate insights, leading to better decision-making. For example, in marketing, AI can analyse customer data to identify trends and predict future behaviour, but only if the data is well-managed and relevant.

2. Informing decision-making
AI can significantly enhance decision-making by providing data-driven insights. But for AI to be effective decision-makers must understand how to integrate AI insights with their domain expertise. AI literacy empowers employees to use AI tools to complement their judgement, rather than replace it. In finance, for example, AI can predict market trends or identify investment opportunities, but the final decision still requires human intuition and strategic thinking.

3. Automation of routine tasks
One of the most immediate benefits of AI is its ability to automate routine tasks, freeing up human workers to focus on more complex and creative work. AI literacy helps employees identify which tasks can be automated and how to implement AI solutions effectively. In manufacturing, AI can optimise production schedules or manage inventory, reducing the time employees spend on repetitive tasks and allowing them to focus on innovation.

4. Innovation and creativity
AI can be a catalyst for innovation by providing new tools and methods for creative problem-solving. For instance, AI-driven design tools can generate ideas or optimise processes that were previously unimaginable. AI literacy ensures that employees know how to use these tools to their full potential, fostering a culture of continuous innovation. In product development, AI can suggest design improvements or predict customer preferences, driving the creation of products that better meet market needs.

5. Ethical considerations and bias mitigation
As AI becomes more integrated into decision-making processes, it’s crucial to address ethical considerations and the potential for bias in AI models. AI literacy includes understanding how AI models are trained, recognising potential biases, and ensuring transparency and fairness in AI applications. This awareness helps organisations use AI responsibly, maintaining trust with customers and stakeholders. In hiring, for example, AI can be used to screen candidates, but without careful monitoring, it could inadvertently perpetuate existing biases.

Encourage AI adoption with hackathons and innovation challenges

Every function and individual in an organisation will be impacted by AI and encouraging them to use it in their daily work so it becomes habitual is crucial. Some of the most common uses right now include increased efficiency, task automation, customization at scale, personalisation, and cost reduction but as AI evolves, so will its use cases. It won’t replace us but it will replace those who don’t use it at all.

Hackathons or innovation challenges can be instrumental in kick-starting and solidifying AI adoption and literacy initiatives. Why? It’s incredibly powerful when you bring together a group of people for a set amount of time to focus on solving a specific challenge. The benefits reach far beyond the actual solutions they come up with:

• Hands-on, practical experience - Participants gain firsthand experience with AI tools and technologies, demystifying AI concepts through direct application.

• Project-based learning - by working on specific projects, individuals learn how AI models are built, trained, and deployed, which deepens their understanding of AI principles.

• Real-world application: participants work on solving real-world problems using AI, which illustrates the practical uses of AI and its impact on their specific role.

• Cross collaboration: Hackathons often bring together people from various backgrounds and experience levels which facilitates knowledge sharing.

• Mentorship opportunities: You have the opportunity for experienced AI practitioners to mentor more novice employees, walking them through tricky concepts and helping them more easily understand how it can be applied.

• Innovative thinking: Encourages participants to think critically about AI's role and potential, fostering a deeper understanding of the possibilities

• Skill Development: These events help participants acquire the necessary skills to contribute effectively to AI projects both during the hackathon and after.

• Awareness of AI tools and resources - Participants gain exposure to various AI platforms, libraries, frameworks, and accessible resources like datasets and cloud tools, which makes it easier for them to experiment and learn.

• Focus on ethics: Hackathons can emphasise ethical AI by including challenges that require participants to consider fairness, transparency, and accountability in their solutions.

• Addressing bias: By involving diverse teams, hackathons help highlight and address biases in AI models, contributing to more equitable AI solutions.

By engaging in hackathons or innovation challenges, organisations can not only accelerate AI adoption but also build a culture of continuous learning and innovation. This ensures that as AI evolves, so too does the organisation’s ability to leverage its full potential.

Shift your organisation's culture

Not every organisation has the luxury of leapfrogging into AI. Most have to consider legacy infrastructure, security risks, data sources, development processes, and the like. But organisations are feeling the pressure to adopt AI and develop an AI strategy, often adding AI features simply for the sake of having AI. This can lead to AI being implemented in ways that feel more like marketing than meaningful innovation. And while AI is a powerful tool that can transform businesses, it’s not a strategy in itself. Organisations find themselves tasked with creating an AI strategy, even when they haven't clearly identified a specific set of problems AI will solve.

Organisation-wide AI adoption is not about developing a strategy or sending every employee through a few training courses. It’s about creating an environment where experimentation, collaboration, and finding practical use cases can thrive. To truly integrate AI across an organisation, you need more than just training programs—you need to prepare the environment for innovation. It is an awareness-led change-management initiative that needs to be embedded into the culture.

Ideathons and Hackathons should form part of every organisation's AI adoption toolkit. It should not only be R&D and IT teams experimenting, it should be every function. Take the same mindset that led an organisation to create an employee AI training program but this time multiply the experience into a social, collaborative, competitive, gamified learning experience that solves a real problem, in real time, with tangible outcomes, in just eight hours. That type of hands-on experience is far more powerful in shifting an organisation’s culture than asynchronous AI courses.

To succeed in today’s AI-driven world, organisations have to think beyond skills training and create an environment where AI experimentation is encouraged, collaboration is seamless, and successful use cases are actively promoted across the organisation. This approach turns isolated experiments into transformative, organisation-wide innovations that will naturally give birth to AI adoption and meaningful literacy.

Training courses on AI completed? Next stop, implementing some curated change management with practical, real learning experiences. Go bespoke to suit the organisational strategy and get this powerful tool into your 2024/25 toolkit. Discuss all your options with Suru.