A Guide on How to Implement AI in Business

Every business leader recognizes that AI is now an essential component for success.

Bizagi CEO Gustavo Gomez recently wrote that “slow adoption creates a real risk of falling behind and a few AI experiments won’t be enough to make an impact. To see its full potential in the enterprise, AI needs to be rolled out in many different business processes”.

However, implementing AI is no easy feat, so where do you start?

What results do you want to see from AI?

Focus on identifying high-impact use cases that align with your business needs and goals. We’ve seen our customers focus on areas where AI not only increases efficiency but provides deeper insights to support better informed, faster decision making. Look for:

1. Repetitive tasks that could be automated, while accelerating or improving business decisions.
2. Areas where decisions rely on lots of data, which may be unstructured and almost impossible for a human to analyze in a sensible amount of time.
3. Customer pain points that need to be addressed faster or more accurately, where it isn’t possible with existing resources.

This ensures that your AI efforts are purpose-driven, practical, and aligned with real business value rather than hype or technology for its own sake.

Assess current capabilities and needs

Before you kick off your AI initiative, consider the resources you have available within your organization to get going. Does your existing team have the skills needed to implement AI or are there knowledge gaps that need addressing?

Consider whether you need to make any new hires or if training is required for your existing team. It’s also important to review whether your current tech stack can support AI implementation.

For organizations without AI specific skills in house, or a will to acquire them, a critical step is to select a technology that enables users without that expertise to create and manage AI solutions using natural language. Bizagi is one example.

Evaluate data access and quality

AI tools are only as good as the data they are trained on, so to get the most out of your AI initiative, you need quality data. Review the accuracy, consistency, and completeness of your data to make sure your AI systems deliver the most reliable results. 

The best thing about AI however is that the data doesn’t need to be structured. Generative AI tools can analyze large documents for example and find the important insights inside, compare different documents and look for patterns, all without a human having to trawl through it.

Something missing from AI technologies themselves such as the Azure Open AI Service, is a way to manage the end-to-end business process, and pull in the data that is required from different systems and files. That is where a process automation platform can provide a huge amount of value.

Consider security, governance and ethics

AI needs clear rules. It is important to establish policies on the acceptable use of AI and communicate these to all relevant stakeholders. This ensures your AI efforts are ethical, secure, and aligned with both regulations and your company values. You’ll need to consider:

• Data privacy and compliance: Control who can view, query and edit data. Use role-based access control and encryption to protect sensitive information.
• Bias and fairness: Regularly review AI outputs and ensure systems are tested against a diverse range of inputs to support fair, unbiased decision-making.
• Transparency: Document how your AI works to build trust among employees, customers and other stakeholders in its decisions. The best AI technologies today can explain their reasoning, enabling a human to assess if the decision is correct or not.
• Security: Build controls to protect your systems from data breaches or misuse of AI-generated outputs.

Evaluate vendors to find your fit

There are now many companies offering AI products and services, and the list grows every day. But which technology provider best suits your needs? Key questions when evaluating vendors include:

1. How does the technology provider keep your data safe and secure?
2. Does the vendor have experience helping companies in your industry?
3. Have they delivered tangible benefits to organizations with similar business challenges? 
4. Will it integrate with your current tech stack and how easy is the integration process? 
5. Can the vendor help you identify the best use cases for AI in your business?
6. Does the vendor offer any support with implementation?

Run a pilot program for AI in the business

Test the value AI can bring to a specific use case to build confidence in the technology and help win support for use in other areas of the business. This experimentation phase allows you to launch and iterate quickly with minimal risk and deliver ROI quickly.

Some companies, including Bizagi, are offering packages that enable pilot programs dedicated to delivering quick results for a modest investment.

Scale AI across the business

Now you’ve demonstrated the value of AI, it’s time to move from isolated use cases to enterprise-wide adoption. Investigate how AI could benefit core business processes, decision-making workflows, and customer experiences.

As the capabilities of AI continue to evolve, organizations that move beyond experimentation and begin to implement AI across diverse business areas and processes will see significant, long-term value.

To learn more about Bizagi’s AI capabilities visit our AI solutions page.