You're trying to improve your business' AI capabilities. How can you find the right platform?

Define your goals

AI capabilities for your business are exciting explorations, but don't just jump in! 

Careful planning and goal-setting are key. Think in stages, like gathering data, building your AI, launching it, and keeping it up-to-date. Measure progress with clear targets, like pre-built models and performance scores. 

It is crucial to always keep in mind the importance of understanding the data you possess. It is essential to know the source of the data and take the necessary measures to ensure its safety. 

Neglecting data security can lead to severe repercussions, including data breaches and loss of sensitive information. Therefore, it is imperative to take the necessary precautions to keep your data secure. 

Assess your resources

"A budget is a plan that tells you where your money should go, instead of wondering where it went." This quote by leadership expert John Maxwell highlights the importance of careful resource planning. When assessing the resources, it's crucial to consider four key attributes:

1. People: Think about the skills, expertise, and experience required for each phase of the project. 

2. Technology: Consider the software, hardware, and other technological tools required. Do they fit within your budget and meet your compatibility needs?

3. Data: Does the project require specific data sets for AI training or analysis? Are these readily available and accessible?

4. Budget: Estimate the costs associated with each resource measured and create an ideal budget formula.

Compare features and functionalities

So, you've shortlisted a few impressive AI solutions, each boasting the latest features and dazzling functionalities. But before you get swept away by the tech specs, take a deep breath & research deeper. 

Here are three practical tips to look beyond the tech specifications:

When shortlisting vendors, ask about their experience, request case studies, and understand their process. A good vendor is transparent about their strengths and limitations.

Next, investigate their reputation & track record. Research their work in your industry, scour online communities for user testimonials, and assess their overall reliability.

Finally, think beyond the initial purchase. Choose a vendor who views your project as a partnership, not just a business. 

Evaluate customer reviews and feedback

Ditch the star ratings and think beyond the box! Don't just skim reviews - seek industry-specific insights from companies similar to yours and tackle problems like yours. 

Look for detailed feedback on the platform's strengths, weaknesses, and real-world performance across diverse use cases. Don't be afraid to ask questions directly! 

Supplement your research with independent analyst reports, online communities buzzing with user experiences, and even social media chatter to get a well-rounded understanding of the platform's culture and customer satisfaction. 

Remember, choosing the right AI model goes beyond features - it's about finding one that truly aligns with your needs and sets your project on the path to success.

Test and iterate

As someone who's witnessed countless project triumphs and stumbles, let me tell you: testing and iterating is the ultimate weapon. 

You need to experience the platform firsthand to feel its strengths and weaknesses under your data and goals. Here's what you need to do:

Free trials and sandbox environments: Experiment with features, train models on your data, and see how the platform handles your specific challenges. 

Pilot projects: Pick a small, manageable project that aligns with your overall goals and dive in with the chosen platform. You'll understand its integration, performance, and impact on your workflows.

Embrace the iterative loop: Testing isn't a one-time thing. As you learn and gather data, refine your approach and strategy.