Software development was measured to be slow, challenging and relies on technical resources as of early 2010s. This led businesses to rely on humans to do machine-like repetitive work in low-income regions which led to challenges in governance, data security and quality.
Technologies like RPA democratize certain types of software development (i.e. automation software), reduce repetitive work and grew rapidly as enterprises chose automation over outsourcing. As analysts witnessed such developments, democratization was ranked number 3 on the 2020 tech trends. An important trend within technology democratization is IT democratization which is about providing non-technical users access to easy-to-use solutions for automation and app development.
Empowering non-technical users to build solutions is powerful but risky. What happens if a core system relies on a poorly documented solution developed by a non-technical user?
To address questions like this, we will explain IT democratization, its challenges and our suggestions on overcoming those challenges.
What is IT democratization?
IT democratization is giving users, who do not have professional training, the ability to build new automation solutions or applications. This is crucial since most processes are run differently in different companies. Democratized solution development allows companies to automate their specific processes without necessarily following boilerplate templates.
Though IT democratization is impactful, it is a continuation of an existing trend. While software development was the domain of mathematicians in the 1940s and 50s, it was later picked up by scientists in different domains as well as computer scientists. Enabling non-technical personnel (e.g. millions who can use solutions like spreadsheets) to develop software solutions is the next logical step in IT democratization.
An analogy is modern photography. Thanks to advances in cameras, people with little to no photography training can take pictures with their smartphones that are sometimes indistinguishable from a professional’s work.
1. Democratization of app/bot development
1.1 Democratization of app development
Democratization of application development gives citizen developers, who have no programming knowledge, the ability to develop different applications, turning them into capable developers.
There are currently 24.3 million software developers globally. However, with the predicted shortage of 500,000 of software developers by 2024, businesses need to start being self-sufficient when it comes to application development.
Through add-ons and no-code tools provided by vendors, capable developers can develop applications to enhance their processes and maintain their competitiveness without necessarily having expanded IT resources.
1.2 Democratization of bot development
Non-technical users have the opportunity to create bots(e.g. RPA bots) to automate their repetitive tasks using no-code or low-code solutions. The result is a more level playing field where smaller businesses with limited IT and financial resources may also take advantage of the effectiveness of relieving their teams of time-consuming manual tasks.
Some use cases of RPA bots developed through drag & drop capability, screen recording technology, and easy-to-use interfaces include:
- Employee onboarding: automating the processes of employing a new team member and bringing them up to speed with the company processes, such as automatically scheduling onboarding sessions.
- Employee offboarding: automating the processes of an employee leaving the company, such as calculating their compensation packages, restricting their access to company data, etc.
- Contract automation: automating the generation of contracts by choosing the nature of the contract (i.e. sales contract, employee contract, outsourcing contracts, etc.) and allowing the software to fill in the blanks of pre-approved templates.
- Financial reporting: automating the creation of periodic financial reports by automatically extracting data from different financial applications.
- Product updates: automating notifying your current customers and potential leads of the latest updates in your products’ line ups.
2. Democratization of data
Data democratization ensures that those that can generate value with data can access it. Certain data can be democratized across the company and others may be shared publicly via data marketplaces.
For example, financial market data used to be accessible in paper form or shared during shareholder meetings. Democratization of financial market data ensured academics to analyze years of financial market data and identify drivers of stock market returns. Similarly, citizen investors armed with stock market data and a social media audience have outperformed established hedge funds.
3. Democratization of data science
Democratization of data science gives non-technical users the tools to analyze data and build machine learning models.
As with any technical development, data science began as a domain restricted to PhDs. However, as technologies like automated machine learning have been developed, citizen data science emerged as non-technical users started building machine learning models via no code or low code interfaces.
4. Democratization of know-how
Although AI consultants exist for companies to employ to aid them in their AI adoption, vendors pushing IT democratization offer free access to knowledge bases, such as forums, communities, and websites, where users can:
- Find solutions to their problems,
- Ask experts for advice,
- Navigate through different vendors,
- Explore automation opportunities and more
What are the benefits of democratized IT?
1. Lower solution development costs
With IT democratization, software development can be done at scale quickly, and at lower costs. For example, most RPA vendors today offer free tutorials on YouTube and their website on navigating the software interface, building a bot, troubleshooting, etc.
Moreover, online communities and forums, too, can help fellow citizen developers with their issues.
This eliminates the need of allocating a budget specifically for hiring an IT team to help you build a bot, maintain it, and customize it.
2. Higher productivity
A typical rules-based process can be automated up to 70-80%. Lower software development costs enable companies to automate more repetitive work, increasing productivity of companies.
3. Increased adaptivity
Lower solution development costs and higher productivity will enable companies to react faster to market conditions, getting ahead of their rivals
4. More data driven decisions
Democratization of data and data science ensures that more decisions can rely on data vs the past when data scientists were the only ones capable of building machine learning models. This will help businesses progress on their AI transformation.
What are the challenges of IT democratization?
Limitations of no code tools
The main challenge of IT democratization is the limited flexibility of its engine, the low-code/no-code tools that enable IT democratization. Therefore, if a company needs to build an complex app, bot or a machine learning model, no code tools may not be the right solution
Before purchase, companies should understand the capabilities of the no code tools that they will rely on. Using them on a PoC would help understand the capabilities and limitations of different tools.
Most no code tools produce vendor specific, closed source code. Companies become locked in to their no code tool vendor after building solutions using that platform since they can not port their apps, bots or machine learning models to other platforms.
Enquire vendors about the portability of their no code solutions. Increasingly, vendors are building no code tools that produce code in open source languages, allowing their buyers the possibility to switch platforms with ease
For more on no-code technology
To learn more about no-code technology and its applications, read:
- Top 15 Low Code & No Code Web Scrapers
- Impact of the Low/No-Code Platforms on the Insurance Sector
- Low/No Code Development: How It Works & Use Cases
Finally, if you believe your business would benefit from the following automation tools, we have data-driven lists of vendors prepared for each:
We will help you in your selection journey:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
To stay up-to-date on B2B tech & accelerate your enterprise:Follow on
Next to Read
Your email address will not be published. All fields are required.