As we prepare to wrap up another year, it’s a good time to reflect and, perhaps, learn a thing or two. As Artificial Intelligence (AI) / Machine Learning (ML) fever continues to permeate virtually every product, service and pitch deck, huge value can be derived from carefully assessing how the cost of adding AI components will actually benefit the quality of our products and the lives of our end-users. To a hammer, everything is a nail. To a Founder or Head of Product, everything should not be an AI/ML application. Here’s an example of how things can go awry:
The CNET Case
In early 2023, CNET, owned by Red Ventures, began experimenting with AI-generated articles for its personal finance section, promoting the initiative as a way to enhance efficiency while maintaining high-quality, factual content. The AI-generated articles, covering topics like credit cards and loans, were intended to save time and mimic expert-authored work. However, the effort quickly faced backlash due to significant factual inaccuracies, such as basic errors in compound interest calculations, and concerns about plagiarism, as some articles closely mirrored existing sources without proper attribution.
Critics highlighted the lack of transparency and editorial oversight, questioning the reliability of CNET’s content and its commitment to quality. The backlash forced CNET to pause the program and issue corrections on numerous articles. The case underscores the risks of overhyping AI without recognizing its limitations. When deployed without sufficient human involvement, AI can undermine credibility, deliver negligible value, and cause reputational harm.
Unlocking Business Value with AI: Quantiva’s Approach to Practical Innovation
Apart from being overused buzzwords, AI and ML are truly transformative technologies. At Quantiva, we guide our clients through the complexities of AI/ML adoption, ensuring they not only leverage these technologies effectively but also avoid the common pitfalls of misaligned implementations.
The Promise and Perils of AI/ML
AI/ML excels in many areas: automating routine tasks, extracting insights from massive datasets, enhancing personalization, and predicting trends. However, it’s not a silver bullet. These technologies can fall short when applied without a clear understanding of their strengths, limitations, and the specific business context. Misaligned expectations or poorly planned initiatives can lead to wasted resources and diminished ROI.
Quantiva’s role is to bridge this gap between potential and practicality. Our philosophy is simple: AI/ML is a tool—not a goal. It’s about solving real problems, not chasing trends.
Quantiva’s Methodology: From Strategy to Impact
At Quantiva, we take a pragmatic and strategic approach to AI/ML implementation. Here’s how we ensure success:
- Understanding the Problem: We start by identifying the core business problem. Is it a process inefficiency? A customer acquisition challenge? A lack of actionable insights? By focusing on the problem first, we ensure that the technology serves the business, not the other way around.
- Evaluating Feasibility: Not every problem requires AI. We assess whether AI/ML is the right tool for the job or if simpler, cost-effective solutions would suffice.
- Aligning AI with Business Goals: Once feasibility is established, we align the AI/ML initiative with the company’s broader objectives. Whether it’s driving revenue, improving customer satisfaction, or reducing operational costs, we keep the business value front and center.
- Data Strategy and Preparation: High-quality data is the backbone of any AI/ML solution. We help clients clean, structure, and manage their data to ensure models can deliver reliable outcomes.
- Iterative Development and Deployment: We build AI/ML solutions iteratively, testing in real-world scenarios to validate effectiveness and fine-tune performance.
- Change Management and Training: AI/ML adoption often requires cultural and operational shifts. We support clients with training and change management to ensure seamless integration.
Success Stories
AI-Powered Software as a Medical Device
Quantiva delivered an AI-powered Software as a Medical Device (SaMD) solution to auto-contour organs at risk, a critical step in radiation oncology. We established an algorithm change protocol, ensured compliance with FDA regulations, and implemented a scalable cloud-based system. Within months, the client obtained FDA 510k clearance, enabling faster market entry for a life-saving tool.
Optimizing Real Estate Investment
A national real-estate investment fund reduced asset processing time from four days to two hours with Quantiva’s help. We restructured their data pipelines, developed AI-driven tools for automatic opportunity discovery, and created a real-time dashboard. The client improved decision-making, enhanced regulatory compliance, and gained a competitive edge in the market.
A Balanced Perspective on AI/ML
At Quantiva, we are champions of innovation, but we’re also realists. We believe that the best AI/ML solutions are those that are thoughtfully designed, strategically aligned, and carefully executed. By understanding where these technologies excel and where they fall short, we empower our clients to unlock true business value—driving results without the hype.
Let’s have a conversation about how AI/ML can transform your business. Contact Quantiva today to explore the possibilities.
Happy Holidays and we’ll see you in 2025 with more innovations, insights, and early-stage business spotlights in our upcoming editions of the Quantiva Quorum.
