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In an era that celebrates lightning-fast technological advances, organizations' data management remains inadequate. Yes, we have moved to data warehouses, big data, data lakes, and now lake houses, but none of this infrastructure has gone far enough.
Data entry is still a tedious and error-prone task that remains prevalent in most organizations. 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 trying to move on without solving the data problem. We may not be catching up yet, but data forces AI, and data problems will prevent you from using AI to stay competitive. Now is the time to get serious about data. If you don't, you'll miss the big wave. AI can actually help you do better with your data.
A complete transformation can take time, but here are three things you can do right away to get momentum on your side and get immediate value.
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Automate AI data collection
Data has long been held back by manual collection processes and the inaccuracies associated with this approach. While the exciting part of AI is often in the algorithms and models, the unsung hero of the AI story is the quality of the data fed to those models.
Proper data collection is more than just a task; it is the foundation of the future of intelligence for any business. When data is accurately captured and managed, AI systems operate at their full potential, leading to cutting-edge insights and predictive analytics.
There are already many AI solutions on the market that can input information into the system. Although these solutions often require investment, the benefits of employee time savings and high-quality data offset any temporary issues.
Prioritizing investments in data collection infrastructure not only future-proofs your data assets, but also prepares you for the next wave of AI innovation with a strong foundation of high-quality data to feed your AI models. .
Monetize new and existing data
Many organizations already understand the power of having clean data and a clean way to enter that data, but many organizations also realize that tools already exist to help them with this process and that their peers are doing great work. They don't understand that they are achieving results. One new tool for data entry that may come as a surprise is generative AI chatbots.
With the advent of Gen AI, a new breed of chatbots has emerged. This is a chatbot that can have high-level conversations that resemble human interactions more than ever before. Not only can you understand customer questions, but you can also enter and collect data directly into your business systems, process forms efficiently, and personalize customer profiles. The integration of AI-driven chatbots like this doesn't just reduce costs, it also revolutionizes customer engagement and unlocks new insights from every interaction.
If the first step is to automate data collection, chatbots can collect and process data directly from customers without human intervention. In addition to collecting data, chatbots can also be used for cross-selling. Cross-selling opportunities through existing data resources are a key way to capture new revenue.
All the data collected from existing clients often sits idle in most organizations, wasting valuable resources. Through conversational AI and existing data in hand, companies can remarket their original services to these clients or provide suggestions for other services that may be of value to them. Working together, these two technologies can create valuable secondary revenue channels, all based on the infrastructure a company already has in place.
Instead of having a representative manually respond to inquiries or collect contact information, we now have an additional team member focused solely on data collection and entry. Your chatbot will work to collect this valuable information for you, so you don't have to worry about constantly updating your data or generating new leads.
Leverage existing data for customer growth
The pursuit of growth often means spending time and money acquiring new customers. But there is untapped potential within your existing customer base and its data. Multi-service organizations are poised to benefit from intelligent, targeted and predictive cross-selling strategies and have unique advantages through the existing data they have.
Imagine a system that not only manages the customer interest pipeline, but also predicts other services a customer might benefit from based on data from previous interactions. Such predictive power comes from AI’s ability to sift through past win-loss records and other analytics to provide actionable insights into cross-selling opportunities.
As a result, the customer data you already have is a rich mine ready to mine for organic growth opportunities. By leveraging predictive analytics, marketing and sales organizations can create bespoke cross-selling models that unlock new revenue streams that previously flowed beneath the surface of the revenue pipeline.
It’s time to modernize your pipeline data
Gone are the days when manual data management was the norm. Instead, AI is poised to bring a more dynamic, efficient, and intelligent future to business operations. Organizations that recognize and act on the opportunities presented by AI in data processing will be at the forefront of this paradigm shift, reaping invaluable benefits of efficiency, customer insight, and most importantly, growth. you will enjoy it.
Investing in AI not only means staying competitive in today's market, but also preparing for the future. As technology continues to evolve, companies that have already integrated AI into their operations will be better equipped to adapt and grow.
Chris Stephenson is Managing Director of Intelligent Automation and AI at alliantgroup and previously served as Managing Principal at Grant Thornton.
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