In an era that celebrates lightning-fast technological progress, organizational data management continues to decline. Yes, we’ve gone through data warehouse, big data, data lake and now even lake house phases, yet none of this infrastructure is moving the needle that far.
In most organizations, the laborious and error-prone task of keying data is still prevalent. Data remains disconnected across departments, data quality is often under scrutiny and employees at all levels of the organization struggle to access insights from the information they receive.
Now, the next big thing — AI — is already here and everyone is scrambling to move forward without solving their data problems. Maybe you haven’t kept up, but data drives AI, and all your data problems will prevent you from using AI to stay competitive. This is the moment to get serious about your data or you’ll miss out on the big wave, and AI can actually help you get it right.
A complete turnaround can take time, but here are three things you can do right away to turn the momentum in your favor and get immediate value.
Automated AI data collection.
Data has long been hampered by the manual collection process and errors associated with this approach. While the allure of AI is often in the algorithms and models, the unsung hero of any AI story is the quality of the data that feeds those models.
Collecting the right data isn’t just a job — it’s the foundation of any business intelligence future. When data is captured and managed correctly, AI systems can operate at their full potential, resulting in advanced insights and predictive analytics.
There are already many AI solutions in the market that can feed information into the system. These solutions often require capital investment, but the time savings from employees and the benefit of high-quality data offset any temporary problems.
Prioritize investing in data collection infrastructure, and you’re not only future-proofing your data assets, but the next generation of AI innovations with a strong foundation of high-quality data to feed those AI models. Also setting the wave phase.
Monetize your new and existing data.
While many organizations already understand the power of having clean data and clean ways to enter that data, many fail to realize that there are already tools ready to help them in the process. And they’re already doing wonders for your industry peers. An emerging tool for data entry, which may surprise, is creative AI chatbots.
With the advent of gen AI, a new generation of chatbots has emerged – ones that can have high-level conversations, that more closely resemble human interactions than ever before. Not only can they understand customer queries, but they can also enter and store data directly with business systems, efficiently handle forms and personalize client profiles. Integrating such AI-powered chatbots isn’t just about reducing costs — it’s about revolutionizing customer engagement and generating new insights from every interaction.
If the first step is to automate data capture, chatbots can collect and process data directly from users without human intervention. Chatbots can not only collect data, but they can also use it for cross-selling. The opportunity for cross-selling through existing data resources is an important source of new revenue.
All data collected from existing clients is often useless to organizations, wasting valuable resources. Through conversational AI and existing data, your business can remarket the original service to those clients or make suggestions about what other services might be of value to the client. Together, these two technologies can create a valuable secondary revenue channel, and all the infrastructure-based companies are already there.
Instead of having to manually answer a person’s inquiries or collect their contact information, you now have an additional team member whose sole focus is on data collection and input. With chatbots working to capture this valuable intel, you don’t have to worry about constantly refreshing data or bringing in new leads.
Put your existing data to work for customer development
Achieving growth often costs time and money to acquire new customers. Nevertheless, there is an untapped reservoir of potential within existing customer bases and their data. Multi-service organizations are meant to benefit from cross-selling strategies that are intelligent, targeted and predictive, and have an inherent advantage through the data they hold.
Imagine a system that not only manages your pipeline of customer interest, but also predicts other services they might benefit from based on data from your previous interactions. Such predictive capability stems from AI’s ability to search and analyze past win/loss records, as well as other analytics, and provide actionable insights into cross-selling opportunities.
As a result, existing customer data becomes a rich vein ready to be mined for organic growth opportunities. By leveraging predictive analytics, marketing and sales organizations can develop cross-sell models that will unlock new revenue streams previously undetected below the surface of their revenue pipeline.
It’s time to modernize the data pipeline.
The era where manual data management was standard practice is behind us. In its place, AI is poised for a more dynamic, efficient and intelligent future for business operations. Organizations that recognize and embrace the opportunities presented by AI in data handling will find themselves at the forefront of this paradigm shift, which will improve efficiency, customer insight, and most importantly , benefit from the irreplaceable advantage of development.
Investing in AI isn’t just about staying competitive in today’s market — it’s also about preparing for the future. As technology advances, businesses that have already integrated AI into their operations will be better equipped to adapt and thrive.
Chris Stephenson is the Managing Director of Intelligent Automation and AI. Coalition group and was previously Managing Principal at Grant Thornton.
Credit : venturebeat.com