The last decade has seen rapid advancements in Artificial Intelligence (AI) and Machine Learning (ML) technologies. With the introduction of generative AI, such as OpenAI's GPT-4, businesses now have access to tools that can create content and interact with customers like never before. As these technologies continue to evolve, it is inevitable that the way businesses procure AI and ML tools will also change. In this blog post, we will explore the future outlook of how businesses will buy AI and ML tools in the next 10 years.

The Rise of Generative AI:

Generative AI, also known as deep learning or unsupervised learning, is a subset of machine learning that enables machines to generate content and mimic human-like behaviour. This technology has made significant strides in recent years, with OpenAI's GPT-3 leading the way. GPT-3 is an AI language model that can generate coherent paragraphs of text and even entire articles. This has significant implications for businesses, as it can reduce the need for manual content creation and enhance customer interactions.

Changes in Business Software:

The introduction of generative AI will also lead to changes in business software. As these technologies become more advanced, they will be integrated into existing software and lead to the creation of new software tools. This will result in more intuitive software interfaces and applications that can learn from user behaviour and adapt to their needs.

One example of this is Salesforce's Einstein AI platform, which uses machine learning to analyse customer data and make recommendations for sales and marketing teams. This technology has already had a significant impact on the sales and marketing industry, and we can expect to see similar applications in other industries as well.

Procuring AI and ML Tools:

As AI and ML tools become more prevalent in business software, the way businesses procure these tools will also change. Traditionally, businesses have purchased software licenses or subscriptions for a set period of time. However, with the introduction of generative AI and other advanced technologies, the pricing model for these tools will likely change.

One possible pricing model is pay-per-use, where businesses only pay for the AI and ML services they use. This model is already in use for some cloud computing services, and it could be extended to AI and ML tools as well. This would allow businesses to only pay for the AI and ML services they actually use, rather than purchasing a full license or subscription.

Another possible pricing model is a revenue-sharing model, where the AI and ML tool provider takes a percentage of the revenue generated from the use of the tool. This would incentivise the provider to create high-quality tools that drive revenue for the businesses using them.

Managing AI Security and Assurance during Procurement:

As businesses procure more AI and ML tools, it is important to ensure that these tools are secure and trustworthy. This requires a collaborative approach between the business, the AI tool provider, and any third-party auditors or certification bodies. Some key considerations for managing AI security and assurance during procurement include:

1. Data Security: Ensuring that the AI tool provider has robust data security measures in place to protect sensitive data.
2. Transparency and Explainability: Understanding how the AI tool makes decisions and being able to explain those decisions to stakeholders, including customers and regulators.
3. Bias Mitigation: Ensuring that the AI tool is designed to mitigate bias and discrimination.
4. Ethical Use: Ensuring that the AI tool is used ethically and in compliance with relevant laws and regulations.
5. Continuous Monitoring: Monitoring the AI tool's performance and security over time to ensure ongoing trustworthiness.

By addressing these considerations during procurement, businesses can ensure that they are procuring AI and ML tools that are secure, trustworthy, and aligned with their ethical and regulatory obligations.

Conclusion:

The introduction of generative AI and other advanced technologies has already had a significant impact on the way businesses procure software tools. As these technologies continue to evolve, it is inevitable that the procurement process will also change. Pay-per-use and revenue-sharing models are just two possible pricing models for AI and ML tools, and we can expect to see more innovation in this area.

However, as businesses procure more AI and ML tools, it is important to ensure that these tools are secure, trustworthy, and aligned with ethical and regulatory obligations. This requires a collaborative approach between the business, the AI tool provider, and any third-party auditors or certification bodies. By taking a proactive approach to managing AI security and assurance during procurement, businesses can ensure that they are leveraging the power of AI and ML in a way that is responsible and aligned with their values.

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