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Dynamics Matters Podcast Ep 119: Unlocking AI potential through low-code development
With special guest Sam Smith, Solution Architect, HSO
In this episode, we discuss:
✔ The role of AI policy documents
✔ Navigating AI hurdles to value and growing confidence
✔ Democratising AI: Low-code platforms as the missing link
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SoundCloud The technological landscape is constantly evolving, with new advancements coming along on a veritable conveyor belt of production.
Artificial intelligence (AI) is the driving force behind the most recent changes, promising to revolutionise many aspects of our lives and work. However, harnessing AI can be complex, often requiring specialised skills and significant resources. This is where low-code development platforms come in, offering a potential solution to bridge the gap and make AI more accessible to a wider range of organisations.
Building guardrails and the role of policy documents
A crucial step towards responsible AI adoption is the creation of a well-defined policy document. This document serves as a roadmap, outlining the organisation's AI strategy and establishing clear guidelines for its use. It should address key areas such as:
- Purpose and scope: Clearly defining the intended use cases for AI within the organisation helps ensure focused development and implementation.
- Permitted users and roles: The policy should specify who is authorised to access and use AI tools, along with their designated roles and responsibilities.
- Training and education: Equipping employees with the necessary knowledge and skills to work effectively with AI is crucial for maximising its benefits and mitigating risks.
- Data governance: As discussed earlier, data security is paramount. The policy should outline measures for data collection, storage, access control, and potential anonymization techniques to ensure data privacy.
- Transparency and explainability: The ability to understand and explain AI decision-making processes is essential for building trust and addressing potential biases.
These elements, combined within a comprehensive policy document, provide a framework for responsible AI development and deployment.
Democratising AI: Low-code platforms as the missing link
While the need for robust policies and a well-defined strategy is vital, there remains a challenge: the technical expertise required to implement AI solutions.
Traditionally, AI development is associated with programmers who have the needed specialised skills. This is a significant barrier for organisations lacking the resources to invest in dedicated AI teams. This is where low-code development platforms come in.
Tools such as Microsoft’s Power Platform, offer a visual, drag-and-drop interface that allows users with minimal coding experience to build and deploy applications. By leveraging pre-built components and functionalities, low-code platforms significantly reduce the development complexity and time required.
In the context of AI, low-code platforms can act as a bridge, making AI development more accessible to a wider range of staff within an organisation. Here's how:
Simplified integration
Low-code platforms offer pre-built connectors and APIs that streamline the integration of AI services. This eliminates the need for complex coding and allows users to focus on building applications around these AI functionalities.
Increased efficiency
The intuitive interface and pre-built components reduce development time and effort. This allows organisations to experiment with AI and identify use cases faster, leading to quicker ROI.
Democratisation of development
By lowering the technical barrier to entry, low-code platforms empower a wider range of staff to participate in AI-powered application development. This fosters collaboration and innovation.
Collaboration and the future of work
The synergy between low-code and AI extends beyond simplified development. As AI capabilities continue to evolve, they can automate repetitive tasks and augment human intelligence.
Imagine intelligent chatbots handling customer inquiries, AI-powered legal research tools assisting lawyers, or AI-driven algorithms optimising marketing campaigns. Just a few examples of how AI can empower human workers to focus on higher-level tasks requiring creativity, critical thinking, and strategic decision-making.
However, the conversation around AI and the future of work requires a nuanced approach. While some concerns exist about job displacement, experts believe the overall impact will be increased productivity rather than mass unemployment. As Sam Smith suggests, AI will likely lead to higher productivity expectations. The focus will shift to how employees can leverage AI tools to create greater value for their organisations.
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