AI
The AI Value for ISVs and Data Providers: 5 Steps to Create Innovative Data-Driven Solutions
In today’s rapidly evolving tech landscape, it's tempting for businesses to chase after the latest trends—Artificial Intelligence (AI) being the crown jewel of them all. However, unless you're an AI and data analytics provider, focusing solely on AI might be a misstep.
AI Should Enhance Your Business, Not Define It
AI is a transformative technology, but it's not a silver bullet. Adopting AI just because it’s the latest trend can lead to poor implementation, low adoption rates, and difficulties in proving return on investment (ROI). Rather than chasing the AI hype, focus on how AI can amplify your existing products and services, improve customer satisfaction, and give you a competitive edge.
Analyzing your current offerings, understanding your customers’ needs for data-driven insights, and monitoring the market landscape can help you identify specific opportunities where AI can make a meaningful impact. AI should serve as the fuel that powers your innovation engine, enabling you to refine and enhance your solutions continuously. So, where do you start?
1. Identify a Use Case with Measurable Value
The first step in leveraging AI is to identify a specific use case where AI and ML can add measurable value. This might seem straightforward, but many companies stumble here, failing to set clear metrics for success. Without measurable outcomes, proving the return on AI investment becomes difficult, jeopardizing future investments.
2. Prioritize Data Quality and Readiness
Once you've identified a promising use case, the next step is to ensure that your data is up to the task. Even the most sophisticated AI models can't compensate for poor-quality data. The old saying "garbage in, garbage out" still holds true, so it’s essential to prioritize data quality and readiness.
Begin by assessing the data required for your AI and ML models, ensuring it’s complete, accurate, and accessible. This may involve setting up the right data connectors, implementing robust data streaming and transformation processes, and establishing strong data quality and governance practices. Reliable, high-quality data is the foundation for effective AI solutions. Missing or poor-quality data leads to flawed insights, compromising trust in AI-driven solutions.
3. Create Analyses Leveraging AI and ML
Creating the right AI and ML models for your use case is crucial to the success of your analyses. However, this process can be difficult, especially if you don’t have a dedicated team of data scientists in-house to create the models and guide you through the process. Fortunately, non-technical users can leverage AutoML (Automated Machine Learning) and GenAI (Generative AI) capabilities to generate insights using platforms designed to simplify the AI/ML process.
AutoML tools like Qlik AutoML automatically handle complex tasks such as model selection, hyperparameter tuning, and model training, enabling users to build and deploy machine learning models without deep technical knowledge. By simply uploading data and selecting the desired outcome, users can quickly generate predictive models that offer actionable insights. Meanwhile, Generative AI tools, like Qlik Answers, allow users to create content, summaries, or even generate creative outputs from simple prompts. These tools can analyze data patterns, predict trends, or generate ideas that help users make informed decisions, all while bypassing the need for coding or advanced data science expertise.
4. Embed AI Insights into Applications
The value of AI is realized when insights are easily accessible where decisions are made—in the software and applications your customers use daily. Ensure that AI-powered insights are seamlessly embedded into your products, making them easy to access, interpret, and share. This not only facilitates quick, informed decision-making but also democratizes AI across the organization, enabling everyone, regardless of technical skill, to benefit from data-driven insights.
5. Focus on Low-Maintenance and Flexible Scalability
To ensure that your AI solutions remain effective over time, focus on scalability and ease of maintenance. Automation and cloud platforms are key enablers, offering the flexibility and scalability needed to grow your AI capabilities in tandem with your business. A scalable, well-maintained AI infrastructure ensures consistent performance and allows your business to adapt to new challenges and opportunities quickly.
Conclusion: Fuel Your Business with AI
The goal isn’t to become an AI company; it’s to be a company that uses AI as a powerful tool for innovation and differentiation. By strategically identifying high-impact use cases, prioritizing data quality, selecting the right capabilities and tools, seamlessly embedding insights into everyday applications, and focusing on scalability, you can create AI-powered solutions that set your business apart. AI should be the fuel that drives your growth and innovation, helping you deliver superior products and services that meet—and exceed—customer expectations.
Qlik is a leader in AI-powered analytics and data integration solutions, empowering over 40,000 customers, including SaaS organizations like ISVs and Data providers, to leverage the power of AI and analytics to drive product innovation, improve customer experiences, and ignite overall business success.. Learn more about how Qlik can partner with you to support your next big idea. Watch the Seamless Intelligence webinar on-demand now.