Use Cases for Generative AI-Powered Automation 

What is Generative AI? 

Generative AI is a subset of artificial intelligence that involves using algorithms to generate new content, ideas, or solutions based on input data. Unlike traditional AI, which typically relies on predefined rules or existing data sets to make decisions, generative AI creates new and unique outputs, such as text, images, music, or even complex solutions to problems.  

This capability makes it incredibly powerful for tasks that require creativity, innovation, or solving novel challenges. By learning from vast amounts of data, generative AI models like GPT-4 can assist in automating processes that were previously considered too complex or creative for machines. 

What to Know Before Getting Started with Generative AI 

Before diving into the world of generative AI, there are a few important considerations to keep in mind. First, it's essential to understand the type of data your organisation has and how AI can leverage it.  

Quality and quantity of data directly influence the effectiveness of generative AI models. It is also important to align AI initiatives with business goals, ensuring that the use cases you pursue will deliver tangible value. Consider the ethical implications of using generative AI, particularly in areas like data privacy and bias. Lastly, investing in the right infrastructure and talent to support AI implementation is crucial for success. 

Generative AI Use Cases 

Generative AI's versatility allows it to be applied across a wide range of industries, automating tasks, enhancing creativity, and solving complex problems in innovative ways. Below are some specific use cases in key sectors: 

Banking and Financial Services 

In the banking and financial services sector, generative AI can be a game-changer. It can automate the creation of personalised financial advice, generate real-time market analysis reports, and even develop customised investment portfolios based on individual client preferences.  

Generative AI can also enhance fraud detection by identifying unusual patterns that traditional algorithms might miss. Additionally, it can be used to automate the generation of financial documents and reports, reducing the time and effort required by analysts and allowing them to focus on more strategic tasks. 

Insurance Services 

Generative AI can streamline the insurance industry by automating claims processing, generating personalised insurance policies, and improving customer service through AI-driven chatbots. By analysing vast amounts of historical data, generative AI can predict risk more accurately, allowing insurers to create more tailored policies that meet the specific needs of their clients.  

It can also help in fraud detection by generating models that identify suspicious claims. Moreover, AI-driven content generation can enhance customer engagement by providing personalised communication based on individual client data. 

Health Services 

Generative AI has the potential to revolutionise patient care and operational efficiency. It can be used to generate patient-specific treatment plans, automate medical documentation, and even create synthetic data for research purposes.  

Generative AI can assist in diagnosing diseases by analysing medical images and generating accurate reports, which can then be reviewed by medical professionals. Additionally, it can be used to personalise patient communication, ensuring that individuals receive information that is relevant to their specific health conditions. 

Energy and Utilities 

Generative AI can optimise operations in the energy and utilities sector by generating predictive maintenance schedules, automating energy management systems, and creating optimised resource allocation plans. By analysing data from various sources, generative AI can predict equipment failures before they occur, reducing downtime and maintenance costs.  

It can also be used to generate models for optimising energy distribution, leading to more efficient use of resources and reduced operational costs. Furthermore, generative AI can assist in automating the design of energy-efficient systems, such as smart grids. 

Government and Education 

Generative AI can transform government and educational institutions by automating administrative tasks, generating personalised learning content, and improving decision-making processes. In the government sector, generative AI can help in policy development by simulating the outcomes of various scenarios, allowing policymakers to make informed decisions.  

It can also automate the generation of reports and legal documents, reducing the workload on public servants. In education, generative AI can create personalised learning plans for students, generate educational content, and even assist teachers by automating grading and administrative tasks, freeing them to focus on teaching and student interaction. 

Generative AI is a powerful tool that can drive significant improvements across various industries by automating complex tasks, generating innovative solutions, and enhancing operational efficiency.  

 As this technology continues to evolve, its potential to transform industries will only grow, making it an essential component of any forward-thinking business strategy. Whether you're looking to streamline processes, reduce costs, or innovate in ways never before possible, generative AI offers a path to achieving your goals and future-proofing your operations. 

The Impact of Pre-Meeting Research on Sales Success

Consistent research demonstrates that sales teams who thoroughly prepare for meetings are much more likely to close deals successfully. By investing in pre-meeting research, these teams gain a deeper understanding of their prospects' needs, challenges, and competitive environment. 

This knowledge allows them to craft more effective and personalised sales pitches that resonate with their prospects, ultimately increasing their chances of success.

What Crystal Knows Does

What if I told you that you could start every meeting with confidence because, in just a few clicks, you can know about the person you’ll be meeting? That’s exactly what Crystal Knows does.

Crystal Knows specialises in helping businesses achieve this level of preparation. By using personality insights derived from public data, Crystal Knows equips sales teams with the information they need to tailor their communication to the unique personality traits of each prospect. This ensures that every interaction is aligned with how the prospect prefers to be approached, making the sales process smoother and more effective.

The Process and Benefits

The process begins with analysing publicly available data, such as social media profiles and online behavior, to create a detailed personality profile of the prospect. This profile provides insights into how the prospect thinks, makes decisions, and prefers to communicate. Armed with this information, sales teams can:

Customise Their Approach

Tailoring your pitch to resonate with the prospect's personality is crucial for successful sales. Crystal Knows provides detailed personality insights that allow you to customise every aspect of your communication. For example, if your prospect prefers direct and data-driven communication, you can focus on presenting clear facts and figures. 

Conversely, if they respond better to a more narrative or relationship-focused approach, you can frame your pitch around stories and the broader impact of your solution. This level of customisation ensures that your message is delivered in a way that feels most natural and compelling to the prospect, increasing the likelihood of a positive response.

Anticipate Objections

Understanding a prospect’s personality also enables you to anticipate potential objections before they arise. Crystal Knows helps you identify traits that may signal certain concerns or hesitations. For instance, a prospect who values stability may be concerned about the risks associated with adopting a new solution. 

Knowing this in advance allows you to prepare responses that directly address these concerns, such as emphasising your product’s proven track record and reliability. By aligning your responses with the prospect’s thinking, you can effectively mitigate objections and keep the conversation moving forward.

Build Stronger Relationships

Building strong relationships is at the heart of successful sales, and communicating in a way that feels natural and engaging to the prospect is key to this. Crystal Knows provides insights that help you adapt your communication style to match the prospect’s preferences. 

Whether your prospect prefers frequent updates, a collaborative approach, or a more hands-off style, you can adjust your interactions to make them feel comfortable and valued. This personalised communication fosters trust and rapport, making it easier to establish a strong, lasting relationship that goes beyond the initial sale.

These benefits lead to more successful meetings, shorter sales cycles, and higher close rates.

Quanton, as a trusted seller, partners with Crystal Knows to bring these powerful tools to your sales team. By leveraging Crystal Knows' insights, Quanton helps you transform your sales process, ensuring that your team is always prepared and equipped to succeed in every meeting.

Do you know where the bottlenecks in your organisation’s processes are?
Can you identify who in your team is underperforming?
Do you have an entire view of your actual process from end to end?
Is a digital twin of your organisation’s processes needed?

Operational intelligence isn’t a nice to have. It’s necessary and a real opportunity to boost efficiencies.

Businesses often face the same issues in any large-scale workflow – bottlenecks, unnecessary repetitive steps, varying team performance, and inefficient data accessibility, among others. 

Imagine having complete visibility into your operations. Knowing exactly where the bottlenecks are, understanding the true performance of each team member and having the ability to make data driven decisions with confidence, and in real-time.

Here at Quanton, our approach, powered by AI-backed process mining integrated with proven methodologies like Lean Six Sigma, is enabling us to turn that vision into reality, providing deep actionable insights into your processes, uncovering inefficiencies and pinpointing areas for improvement, leading to smoother operations and better outcomes.

It starts with insights – and for us that means process mining and reviewing the workflow from end-to-end to find out how workflow really happens – not how it’s meant to happen, or you think it. 

Discovery and analytics

Process mining is a top down, system-based approach which collects system data from all your systems and event logs. That data is ingested into a tool which then applies machine learning AI algorithms to analyse and visualise the data, creating simple dashboards for the business to get valuable insights.

Task mining, meanwhile, is a bottom-up approach which records users work, adding that to the process mining to provide a more complete end-to-end view of processes in your organisation. 

Using process mining you can gain a wealth of data about how processes in your organisation are working. 

Many companies already have dashboard which provide that viewpoint, of course. But while they give businesses a really good view of what has happened, they don’t provide any other details and show you why it happens, how you can mitigate or fix it, or where the bottlenecks are.

That’s where process mining comes in and is really powerful. 

You don’t have to spend a lot of time on spreadsheets, come up with pivot tables or use visualisation tools to configure and build a visualisation or dashboard from scratch. All the heavy lifting is done for us, with AI as the enabler to provide the visual to quickly identify issues and problems in processes.

Using the data previously ingested into the tool, AI can map out the process in seconds, rather than requiring a business analyst to manually create the process map through interviewing process owners.

For businesses to get an in-depth analytical view of their process manually is almost impossible because of the rapid changes in processes, people, systems or technology applications. With process mining, all we need is that live injection of data from systems or applications and you get a constantly updated view into your processes.

For management it provides an ability to identify issues and understand how their business, and processes, operate.

For business analysts it can be a tool to deep dive into a process looking at anomalies so they can have meaningful conversations with business about the processes having already done prep work.

And for process owners, it enables them to identify bottlenecks and issues in their own processes and find solutions and improvements themselves, or work with the process improvement team to solve issues. 

Prediction and simulation

Taking things a step further, more advanced techniques and AI functions will enable you to create effectively a digital twin for your organisation, enabling you to model planned changes and improvements before you implement them, so you can assess the full end-to-end impact before making changes.

Once you achieve that level of maturity, the organisation can become truly proactive and forward-looking.

Of course, the more data attributes and the richer the data you provide, the more in-depth you can dive into a process and the more information you can garner, but you don’t need a lot of data, it really depends on transaction volume. For some smaller processes you may need a month to three months of data to get meaningful views, while for large transaction volume processes a week of data may suffice.

And it’s important we note that these tools are not going to replace BAs – we still need people who have business knowledge and understanding of the processes to find the answers, because AI can’t (yet) tell us what to do to improve the process. 

Through understanding – truly understanding – how your business operates in real time, you can more easily see, and decide, which levers to pull, whether technology, people, processes or data.

It’s an opportunity to really make data driven decisions, rather than decisions based on historical data, experience and assumptions. 

Quanton's operational intelligence process is already in action with New Zealand organisations, including a tertiary provider which has seen benefits across its organisation. You can read all about their journey here.

Call centre quality assurance is a critical component for most call centres, whether regulated or not.

But it’s also a time consuming, costly, resource intensive process, manually listening to calls from agents and marking scores on a scorecard system. It’s a process that can easily take 30-40 minutes for a 10-minute call.

Even with the best of intent, most general function call centres audit only around one percent of all their calls, leaving 99 percent of calls unmonitored – and potentially exposing your organisation to risk, including poor customer experiences.

Specialised contact centres which are heavily regulated may be auditing at a costly expense 25-80 percent of calls, or even 100 percent depending on requirements, but they’re the exception to the rule.

There’s also another flaw inherent in the process.

Often call centre workers are required to follow a script on which they’ll be marked. Fail to follow the script and that impacts their KPI and performance review. But in following the script conversations may be stilted or unnatural, with agents asking random questions which don’t fit into the flow of conversation.

Consider too, the data gold mine that is your call centre, with potentially millions of calls sitting in in your file repository. That’s data that could potentially be mined and provide a wealth of insights for your business.

What businesses need in the modern world is a cost-effective, scalable and reliable solution that can not only QA 100 percent of call, but also derive near real-time information from calls to inform the business so they can make rapid decisions – whether strategy, marketing or customer service.

And that’s where QBOT® (Quality Bot) comes in. It’s an AI-powered compliance and quality assurance developed by Quanton, leveraging a locally developed AI algorithm to accurately assess calls based on an organisation’s QA and compliance regime.

100 percent auditing, with a 50-70 percent reduction in time and cost

The solution we have developed provides a near real-time dashboard for QA and the contact centre performance, which as well as enabling you to audit 100 percent of calls, can detect customer and agent sentiments and create triggers around potential issues, while presenting insights mined from those calls so you can understand your customers better – and build new efficiencies into your business.

QBOT, which is already in use at a number of customers, including Momentum Life, works with existing call centre platforms such as Genesys and AWS, so you can sweat those platforms.

Calls are saved in the call recording repository. Our AI and machine learning solution then turns the audio into text and analyses calls, putting them into an intuitive dashboard to provide the insights for your business.

Via a simple to use portal, and in as little as a minute, you can get a good idea of what the call was about – the reason for it, how it was resolve and intimate analysis. Call summaries and the AI scorecard viewed on the same page, along with the transcript and audio files.

The AI will also provide a self-assessment of its confidence on the call transcript, and we’ve seen great results for heavy accents. Different language models can also be used – some organisations for example have Korean Chinese call centres and our system can transcribe and translate calls into English for QA and analysis.

Mining for insights

All the information you’re collecting via your call centre can provide valuable insights for improving your business.

Consider the example of a customer calling in because their broadband isn’t working. They’re assisted to replug the modem and the issue is resolved.

Those insights can be used to reduce customer calls through providing them with that advice – say through a chatbot – before they call in, so only the more complex issues get sent through to your call centre.

One issue a lot of call centres have is categorising calls, with large numbers of calls often ending up in the ‘other’ or ‘general’ category. That might be because agents are having challenges selecting between the different categories.

We can train the AI to identify the team a customer needs to be talking to – whether customer service, technical support, sales or onboarding, based on existing call centre categories.

That simple step makes a huge different to the call centre in understanding the drivers of why customers are calling and putting in measure to reduce call numbers.

AI can also be used to handle call summaries, so agents don’t have to write up notes, and ensuring consistency, and to mine post-call action items. We can add a trigger for action items to trigger an automated workflow or automation in your CRM system, for example, to automatically send out follow-up documents or text message, reducing the time your agents have to spend doing those processes and freeing them up to help customers.

Resourcing wins

With the near real-time view of call centre operations, call centre managers can quickly identify where resources are most needed and divert resources there as needed, leading to better workload management.

Opportunities for coaching or training of employees can also be quickly identified and if an employee is struggling on a particular day, call centre managers can quickly step in to provide assistance and support.

For the contact centre, QBOT is all about enabling you to run quality assurance across 100 percent of your calls, while getting near real-time sentiment and performance results, identifying coaching opportunities and knowing your customers and the drivers of the calls.

For managers, it enables use of customer insights to steer business decisions and strategies, the building of a culture of continuous improvement and mitigation of regulatory and compliance risk.

And there are benefits for sales, marketing and R&D too. Coupled with closing more deals through understanding key customer behaviour, and insight driven product and service development.

And it’s all here and now – a real life AI solution for your business. If you’d like to see how Momentum Life put it into practice, you can read the case study here.