It is inevitable that people in your industry are leaning into AI to improve customer experiences and save time internally. Embarking on an AI project can be an exciting endeavor that many brands are curious about, but ensuring success requires careful consideration of key factors.

Here are five essential aspects to strategize and align on before venturing into an AI project for your business.

1. Purposeful alignment with your business objectives

Before delving into AI, define a clear purpose and what you’re trying to solve. Implementing AI just for the sake of it isn’t strategic; in fact, it might end up being a costly investment that falls short if not aligned well with your business objectives. At O3, we create a detailed mapping of customer journeys, identifying gaps and pain points that drive the following use cases.


AI can enhance a user experience and drive ROI by leveraging profile and behavioral data in order to tailor content or whole user experiences to adapt to meet the needs of specific users in order to drive conversion and engagement.


Primarily employed for up-front sales or customer support or simply knowledge-base assistance, AI in a conversational context can elevate interactions by introducing a dynamic discussion without the need for extensive condition engineering (think about all those decision trees you can now bypass). It not only adapts responses in real-time but also records customer nuances to inform future interactions. This strengthens the bond between customers and brands by addressing their concerns before they reach a human (if they ever even have to).


By leveraging user data and habits, automated predictions can extend beyond simply suggesting products to anticipating behavior and providing a series of “next best actions” across an experience. This allows for a personalized journey for the user and a data set for businesses that inform product and service decisions.


AI-driven automation streamlines processes across channels, making employees more efficient and prolific. From generating tedious, routine tasks to tackling more complex tasks like document analysis and legal evaluations, AI opens up a world of possibilities for the future of the workforce.


2. Crafting the desired experience: Humanizing AI

When crafting the user experience with AI, treat it much like designing a digital product or marketing experience. with one significant exception. While the workflow is similar, there is a need to consider and thoughtfully design the human interaction. It’s important to note that you can’t account for every interaction, so it’s important to consider the framework and context first. Define the workflow, identify ideal inputs and outputs, and align the AI’s responses with a human touch, reflecting the brand’s voice to enhance engagement. Following the pragmatic approach of treating AI as people, particularly in personalization and conversation, ensures a more effective and relatable interaction, resonating with the brand’s identity.

“Treat AI as people since that is, pragmatically, the most effective way to use the AIs available to us today.” – Ethan Mollick

3. Data, security, and accuracy: The backbone of an AI operation

In addressing data, security, and accuracy for optimal AI performance, the early decision on data usage and availability influences architecture design. Considerations may include the need for proprietary data, guiding platform selection based on privacy concerns, and prioritizing customer information safety. This would require architecture, data and information management processes that are not only secure but regularly monitored. Additionally, accuracy is a key consideration. Getting an LLM to provide an end-user with a specific desired response requires focused training. Depending on the use case, preparing a dataset of 20-100 example questions and answers, especially for LLMs, serves as a valuable tool to assess and refine AI functionality, ensuring consistency in desired responses and influencing output refinement.

4. Strategic project management, cost, and outcomes

Realize that every AI project comes with a certain amount of risk. So, every AI project should have a phased approach. Begin with a workshop to define use cases and desired outcomes, followed by a feasibility study and proof of concept. Evaluate scalability issues early on and make necessary adjustments. Understand the short and long-term investments required for AI projects, and develop an architecture that ensures scalability while managing costs effectively. Regularly review and refine your AI project to align with evolving needs and expectations.

5. Legal and ethical compliance: Navigating the regulatory landscape

Consider the legal and ethical implications of your AI project. Ensure compliance with terms and conditions, aligning them with evolving legislation. Collaborate with a legal expert who is well versed in evolving AI law to navigate the regulatory landscape, utilizing their experience in creating the appropriate contract with the humans that engage with AI systems. Mitigate bias and establish trust, understanding that transparency about your intentions is key. Ensure that your AI project not only complies with regulations but also fosters positive experiences for everyone involved.

The realm of artificial intelligence offers boundless opportunities for innovation, but success hinges on strategic planning and alignment with key principles. By addressing the five crucial considerations outlined above, you not only fortify your AI initiative but also pave the way for a superior customer experience. If you’re interested in learning more about how AI may fit into your strategic objectives, contact us for more insight.

About O3

Since 2005, our team has been pushing the boundaries of innovation with its deep understanding of the current and emerging digital ecosystem. Learn more about us, our work or innovation at O3.