Smarter Data Workflows: Key Findings
92% of companies plan to increase their AI investments over the next three years. But only 1% say they’ve fully integrated AI into their workflows in a way that drives real business outcomes, according to McKinsey.
So why not start with data? It’s where speed, clarity, and accuracy have a direct impact on decisions. AI agents are already helping teams skip the back-and-forth, ask direct questions, and get clear answers without adding more manual work.
Editor's Note: This is a sponsored article created in partnership with Adverity.
Here’s how AI starts pulling your team out of the dashboard swamp:
1. Have Real Conversations with Your Data
According to Adverity, interacting with data should be as straightforward as having a conversation. Teams can get trusted answers quickly with visuals and recommendations using conversational and agentic AI.
Leveraging insights from the Adverity platform, here's what that looks like in action:
- Faster Insights: Teams can get answers up to 60% quicker with natural language queries. No technical or BI skills required.
- Agentic Workflows: Automate campaign reporting, set up alerts, and receive AI-powered recommendations. This can reduce manual work by up to 40%.
- More Self-Sufficient Teams: Marketers create and save reports independently, cutting analyst dependencies by 40%.
- Lower Costs: Data teams are freed up, resulting in a 25% reduction in reporting overheads.
- Seamless Scaling: Easily integrates with your existing data infrastructure as your business grows.
- Real-Time Collaboration: Instant answers enable faster decisions and quicker project delivery.
2. Simplify Data Transformations with AI Guidance
Data transformation can be complex and slow. Adverity’s AI-powered Transformation Copilot lets you describe what you need in plain English, then generates the exact steps to make it happen.
This speeds up your work, cuts errors, and improves data quality. To get started, have your team try describing a common data change in natural language and see how quickly the AI handles it.
3. Avoid Reporting Issues with Smart Naming
Messy or inconsistent naming is a common reason reports get messed up. If you set clear naming rules and stick to them from the start, ideally with tools that check as data comes in, you will save yourself from chasing down errors later.
The key is to get the basics right early and keep everyone on the same page.
4. Proactively Monitor Data Quality
Manual data checks usually happen after errors cause problems, which wastes time and hurts trust in reports.
According to Adverity, automating quality monitoring with AI can catch issues early, before they impact decisions. To stay ahead, set up automated alerts that flag unusual data so your team can fix problems immediately. Here’s what to focus on:
- Automated Monitoring: Spot problems like duplicate data, inconsistent volumes, invalid entries, and late arrivals before they cause headaches. Plus, you should have the flexibility to set your own rules.
- Data Quality Tracking: Investigate problem areas or export data to build dashboards for a detailed view.
- Custom Alerts: Get notified right away when something’s wrong. You decide who receives the alerts, the severity of the issue, and the next steps.
- Scaling Made Simple: Apply changes across teams and markets without repeating the same work.
- Smart Scheduling: Automate data delivery with a system that adjusts itself automatically.
- Flexible Controls: Set your own standards for what good data is and customize checks to keep everything accurate and reliable.
5. Instantly Harmonize Data Across Sources
Data integration is often a tedious, manual job: mapping dimensions and metrics across multiple sources, reconciling differences, and hunting errors.
Adverity’s platform automates this process, handling the complex mapping behind the scenes so your team doesn’t have to. This speeds up integration, reduces mistakes, and turns a slow, error-prone task into something fast and reliable.
That way, your team spends less time wrestling with data prep and more time extracting real insights.
Most data teams waste hours on manual tasks that slow growth and drain resources.
That’s where AI-powered automation and smart admin tools come in, helping agencies grow faster by enabling them to copy workspaces, edit data streams, and manage everything from a single place.
This reduces setup time, limits human error, and ensures data consistency across clients and markets.
Embracing these tools is a practical step toward true data maturity and smarter scaling.
