If you asked most people how much artificial intelligence (AI) has helped them at work lately, they would answer, “Not much.” Even with years of progress and development, it’s still far too hard for the vast majority of businesses to actually take advantage of machine learning. Plain and simple, the technology is out of reach for most companies.
Fortunately, it looks like that’s going to change soon. Experts anticipate that augmenting human intelligence with artificial intelligence will become a common and essential aspect of the next-generation workplace—even at companies without data science experts.
Unlocking the full business potential of artificial intelligence is only achievable when non-technical employees have easy access to AI capabilities. Soon, every employee will be able to build and deploy their own AI applications without writing a single line of code.
Gartner predicts that by 2023 “the number of active citizen developers at large enterprises will be at least four times the number of professional developers.” How is that possible? It’s all connected to the next major trend in AI, democratization—that is, making AI more practical, affordable, and accessible to everyone. Here are some ways successful democratization will help both companies and their employees.
Traditional barriers to software development have prevented non-technical employees from developing their own purpose-built applications—tools that make their jobs easier or improve their performance. AI creates new opportunities for growth by uncovering upside in business data, maximizing process efficiency, and automating time-intensive tasks.
Today, when employees need help with automation, they turn to IT and Data Operations professionals for application development, data pipeline work, and analytics-based insights. These requests often aren’t a priority for the IT and Data Ops teams, who are busy with strategic initiatives driven by management. The new ideas go to the bottom of the queue and remain unaddressed.
A new revolution in the democratization of AI programming is changing this reality, making it possible for anyone to execute automation and capture efficiency gains. The no-code approach to rapid AI development means regular employees can easily add machine learning to existing assets, connecting them to once-inaccessible technologies. They can leverage predictive analytics and develop their own purpose-built interfaces, all without writing a single line of code (or leaning on IT and Data Operations for support).
This no-code movement—the democratization of access—represents a logical but unprecedented shift in how companies approach business application development. What emerges is an empowered workforce imbued with greater productivity and resources for innovation, effectively unlocking the creative capacities of every employee.
Even with existing limitations to application development, most companies already have the data and foundational technologies they need to start using AI throughout their operations. According to Forbes, improving an organization’s business “usually isn’t a matter of building something new from the ground up so much as recomposing those existing assets in new ways or connecting an old system to a new one.”
There are three steps that companies can follow to begin taking advantage of no-code platforms for universal AI application development:
No-code platforms are designed to facilitate this process—not through a single, centralized effort on the part of IT, but by providing employees with broad access to AI development tools that require no coding experience. The best no-code platforms have friendly interfaces that are incredibly easy to use, allowing employees to focus on delivering real business value with their applications.
This capability will soon become commonplace, in what Gartner describes as “the composable enterprise,” where employees are both empowered and encouraged to innovate using no-code platforms for AI development, improving business processes from the ground up at exponential rates.
Often, the data a business already has is an untapped goldmine. According to research firm IDC, only 0.5% of all data is ever analyzed and used, in part due to the fact that the large majority of data is unstructured.
In an operational setting, this data is generated by everything from sensors to customer interactions. It’s important for businesses to have data processing tools that can handle different types of data so that employees can access the data they need, when they need it. The goal is to democratize data—to make it available to as many people in the organization as possible, regardless of their role.
Access to data fosters both ideation and experimentation. When employees have data at their fingertips, they can begin to tinker with it to see what insights they can glean. With the right platform, they can also start to build simple applications that automate tasks or visualize data in new ways.
No-code platforms make it possible for employees to develop applications without any coding experience—and this is crucial for democratizing AI development within an organization. In the past, AI application development has been the domain of a select few individuals with the requisite skillset. This has led to stagnation in innovation, as well as frustration among those who feel left out of the process.
By contrast, no-code platforms open up AI development to anyone in the organization who has an idea for how it could be used to improve a business process. All that’s needed is a willingness to experiment and a bit of creativity.
The best no-code platforms provide users with drag-and-drop interfaces and point-and-click functionality. This makes it possible for even the most non-technical employees to quickly develop working prototypes of their ideas. And because these platforms don’t require any coding, there’s no need for IT approval or sign-off—employees can take their ideas from concept to implementation quickly and easily.
One of the best ways to learn is by doing—and this principle extends to learning how to use AI effectively within your organization. The goal should be for employees to start small, with bite-sized tasks that are well within their comfort levels. As they become more comfortable working with AI tools and techniques, they can gradually expand the scope and complexity of their projects.
This iterative approach not only drives efficiency gains (as employees hone their skills on real business problems), but it also provides an opportunity for feedback so that companies can continuously improve their offerings. Additionally, by breaking down projects into small pieces, companies can avoid costly mistakes that could set them back significantly if left unchecked.
Beyond technical complexity, a second barrier to AI adoption is the ability to understand how well an AI application actually works. Traditional metrics for performance are deeply technical and require a data scientist to interpret. Data scientists are in short supply and often do not understand the application domain.
The performance of AI needs to be communicated through the lens of a business's unique data. The missing link between the results of AI processes and employees’ understanding of those results is “explainability.” Fortunately, the latest no-code platforms surface performance metrics in a way that is clear and easy to understand.
AI-driven insight empowers every employee (from entry-level support staff to C-Suite executives) with a deeper understanding of business value creation. With AI they can better predict the future. With insight, they can change the trajectory of the business.
What does democratizing AI mean in terms of real results? When workers focus on business goals rather than the technical requirements of software development, they can spend more time on value-adding activities while delegating routine tasks to AI-enabled automation.
After all, every role within the modern organization includes some level of repetitive work. Here is a closer look at how democratizing AI can help with four business processes common today.
Lead Scoring: Scoring leads is the process by which companies struggle to focus their efforts on the prospects most likely to purchase their product. With no-code tools, sales and marketing employees can develop and launch custom AI solutions for scoring leads, and even automate routing of those leads to the appropriate stakeholders. Those stakeholders can then act on them quickly, in an informed way.
Preventing Churn: For service and subscription businesses, it's incredibly important to minimize customer churn. With no-code AI, Product Managers and customer support staff can leverage past customer data to create AI models that predict which current customers are most in danger of leaving and why. They can then take the appropriate actions to retain those customers.
Employee Retention: HR professionals sit on massive amounts of data—from hiring pipelines, employee histories, performance reviews, and other sources. No-code AI platforms allow these non-technical employees to innovate how they predict attrition, improve hiring, and enhance employee performance.
Automating Text Feedback: Most of the ways businesses interact with their customers involve text—from support emails to tweets to reviews. No-code AI makes it easy to automate text processing, easily classifying customer feedback or sending negative tweets directly to support.
As AI adoption grows, business leaders must shift their view of AI as a complex, centralized tool to one that is widespread and accessible to every employee. By democratizing AI through no-code platforms, companies can grow their business value exponentially rather than incrementally.
At Akkio, we believe AI is the future—and the future belongs to everyone. Our easy-to-use, scalable, and affordable no-code AI platform can provide your teams with state-of-the-art AI capabilities once reserved for the largest corporations. Try Akkio to experience how easy it is to leverage the power of AI throughout your business.