This much I know: 9 leadership lessons from global CEOs
From absorbing stress to finding your authentic voice, nine leaders of global companies share the wisdom that has helped them excel in their roles. ...
Brain Circuits
Is AI at your service?
Building your own AI models in-house requires deep pockets, access to vast swathes of data, and the right talent. For many organizations, it’s much more practical to use a third-party solution. Annabelle Gawer explains the potential and the pitfalls.
What is AI-as-a-Service?
AI-as-a-Service (AIaaS) is a subscription model that allows startups, SMEs, and even multinationals to use AI to gain insights, enhance efficiency, and create innovative products and services without the expense of developing algorithms.
How does it work?
Think of AIaaS as an extension of cloud-based services. The tech giants built these systems for themselves as data storage and processing solutions, then realized they could turn ‘the cloud’ into a lucrative business opportunity by making their services publicly available on demand. AI is simply an extension of this. AIaaS is also delivered through the cloud, reinforcing the advantage of Big Tech platforms.
Where do I start?
It can be as simple as logging in to the subscription service you are using (such as ChatGPT), asking your query, and getting an answer. The same goes for the AI image generator DALL-E, developed by OpenAI.
What else do I need to think about?
- The right provider
Finding the right provider may depend on the industry you’re in. If you want something tailored to your vertical – for example, health or insurance – you may require a specialized AI provider.
- Data privacy and security
Relying on external AI services requires sharing sensitive information with third-party providers, which could increase the risk of data breaches. Make sure the organization is properly educated in best practices regarding AI data security.
- Over-reliance on one provider
Don’t put all your eggs in one basket: spread the risk. Opting for several providers ensures you’re not at risk of losing control of all the data you generate using their algorithms.
- Read the fine print
Be mindful of the fine print when signing up with third-party providers. Remaining free to switch is essential to maintain strategic autonomy from the giant providers and puts you in a better position should ethical and accountability questions arise.
- Build in-house expertise
Not everyone is equipped to use AI services, so find in-house specialists and data analysts who can navigate AIaaS.
- Retain a human touch
Make sure people you trust check any AI output before you use or publish it. Remember: you are liable for the outputs!
Key learning
AI-as-a-Service can improve efficiency, reduce costs, and improve your decision-making – but it’s crucial to assess the benefits and repercussions it will bring as it evolves so you’re ready for the next wave.
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