Today AI is everywhere and is almost an integral part of our lives. From recommending what to watch next on Netflix to revolutionizing the way we diagnose life-threatening illnesses such as cancer, there are few areas of our lives that AI has improved or, at the very least, impacted.
Businesses of all sizes and types are also leveraging AI to not only develop new products and services, but optimize back office processes and boost productivity everywhere from newsrooms to the manufacturing floor.
What is Applied AI?
The term “Applied AI” encompasses all the activities underlying the operationalization of AI from experimentation to production. In other words, applied AI is not just about the theoretical coverage of AI/ML, but it runs on your actual data and delivers real-world results and outcomes.
AI is making machines around us smarter. While this is common knowledge, what many don’t understand is that artificial intelligence is more of a concept, and applied artificial intelligence is what puts AI to work in reality. Applied AI leverages the capabilities of software applications and powers machine learning, making it highly accurate and adaptable. It is applied AI that is transforming business processes as well the modern society.
Why Applied AI is important and relevant
Applied AI doesn’t have to be ‘exclusive’ only to those who are technically competent or experts in AI/ML programming languages. Low-code/no-code machine learning platforms allow non-AI experts to create AI applications from predefined components. Such platforms are based on an intuitive graphical user interface in designing the application and visual programming as opposed to hard-coded programming techniques. When it comes to developing AI solutions, increasingly, more people will be able to create AI applications and use AI technology, freeing up highly trained coders to focus on the hardest problems.
Did you know that by 2024, more than 65% of applications will be developed using the low-code/no-code development approach. Also, by the same year, it is expected that more than 75% of large enterprises will use at least four low-code/no-code development tools.
During the global coronavirus crisis, the need for software development has driven growth in demand for low-code/no-coding development platforms. As a result, the global low code development platform market size was worth USD 16.3 billion in 2021. It is estimated to reach an expected value of USD 148.5 billion by 2030, growing at a CAGR of 27.8%
Generational shift in workforce
Pandemic followed by the great resignation has taught us the how fluid work environments could get and the need for adapting to the challenges that are thrown at the business environment has become more important than ever. Hiring junior team members from millennial and Gen-Z workforce is no longer the same as previous generations and need to adapt to meet the generations’ expectations is very important for growth focused organizations. Applied AI is the most important way to adapt processes to meet the expectations of the next generation workforce, by eliminating or minimizing rudimentary tasks form day to day jobs of the team and focus on the knowledge centric high value activities.
Examples of Applied AI projects in practice
We, at Invati help facilitate non-technical but experienced senior executives and managers design, develop, and implement AI solutions Examples of some of the Applied AI projects that can benefit a Private Equity firm and can be implemented quickly:
- Reading and classifying incoming Invoices – with the help of Microsoft AI builder or Form Recognizer, one can watch a designed mailbox or set of user mailboxes and proactively classify invoices as they arrive. The complex process of expense management for funds can be automated with ease and this system can be quickly implemented minimizing the effort that finance teams do this manually typing numbers into spreadsheets and running complex formulas. As an added benefit CFO organization will have visibility into these invoices as they arrive.
- Workload Management is rarely considered a need for most organizations until a key team member reports a burnout. In private equity firms where team is subject cyclical workloads, month end, quarter end, year end and so on and then projects, capital raising support, and so on, and there are priority investor support requests. Having visibility into what is on each of teams’ members task list and deadlines, is important for management to monitor to make smart decisions and planning the correct team size. A simple AI model using AI builder or Azure Cognitive services can enable such intelligence to the organization with minimal effort.
- KYC, Compliance Forms, and paper/scanned documents processing can be simplified by enabling the automated document recognition and processing. For example, during onboarding investors to new funds, teams generally get a lot of pdf wet signed/scanned documents arrive by email. An AI bot in Microsoft Office 365 can read these documents and extract data and based on the email content and document type, can create actionable task to the team. Workflows can enable simple reviewing and ingesting the data to the target systems is easier than ever.
- Chatbots based actionable notifications, it could be sending a reminder to an investor about KYC clarification or identifying an email that you missed yesterday that requires a response or answering a HR policy question – AI powered chatbots are readily available at your disposal, and most likely the company is already paying for it. So why not use them to improve productivity of your team?
- Identifying prospective investors is another area that AI today can readily do. The number of Americans with $1 million or more in investible assets surged to a record 14.6 million in 2021, up from 13.3 million in 2020, according to a report from wealth research firm the Spectrem Group. Modelling a criteria to identify who in the pool should be targeted can help in capital raising for new funds and developing new products.
Benefits of Applied AI
Several benefits like accuracy, cost-saving, and better decision-making come bundled with Applied artificial intelligence. In a dynamic business landscape, these are the benefits applied AI offers to industries:
1. Better Decision Making: A lot of tasks would happen smoothly if machines had human-like judgment capabilities and that is exactly what applied AI brings to the forefront. It ensures reduced errors, predicts close to accurate outcomes, achieves end-to-end process automation, and creates a smart ecosystem.
2. Accuracy and Precision: Applied AI bridges the gap between the digital world and the machine world while reducing errors, social ethics, and human bias in the process.
3. Sharp Efficiency: Throughout all the stages of business processes, Applied AI accelerates efficiency while saving time, effort, and money.
4. Augmenting Human Skills: Applied AI helps in automating mundane and repetitive tasks to free up employees. While computer systems powered by AI handle tedious tasks, employees can devote their time and effort elsewhere to increase the business ROI.
5. Lower Cost: Applied AI lower cost of by identifying and solving complex business problems, faster than humans, through its machine learning capabilities.
What’s next?
Low code/No Code Applied AI solutions help organizations significantly reduce the time to market of AI solutions, allow significant cost savings on hiring software and AI/ML experts, yet, it offers the speed, simplicity, and flexibility of ready-made software solutions in a customized manner.
An interesting perspective is that no/low-code AI platforms can help any organizational set-up to kick off an AI initiative; especially for the majority of organizations that lack a formalized AI practice. Such available platforms help them build better applications and solutions quickly without any coding experience or infrastructure, at a much lower cost and more visible impact.
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