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What is the Impact on Tech Work if Everyone is a Tech Professional?

The rise of artificial intelligence (AI) could unlock incredible new abilities for workers everywhere. This article explains, What is the Impact on Tech Work if Everyone is a Tech Professional?

The rise of artificial intelligence (AI) could unlock incredible new abilities for workers everywhere. Business leaders may have heard about increasingly sophisticated no- and low-code tools that allow even employees with little coding knowledge to quickly spin up simple apps and services; as AI makes these tools more capable, we could see a new era in which every worker is empowered to use technology to advance their organization’s goals.

That future seems fantastic at first glance: who would not want teams fully capable of creating whatever they need, whenever they need it? However, there are nuances to this democratization of technical tasks that are well worth exploring. How can leaders and executives prepare to lead organizations where every employee is, to a much larger[AH2] degree, a tech professional?

The Democratization of Tech Skills

In 2018, Microsoft released Power Apps, a no-code app-building platform; in one notable case, a security guard at Heathrow Airport used the platform to build apps that made his job far more efficient... and was promoted to a technical role as a result. Power Apps gave a company’s administrators some ability to regulate employees’ app-building (such as which databases they could access), but they could not prevent these newbie coders from doing whatever they wanted.

According to Microsoft, this “controlled chaos” was by design; in theory, if a sysadmin could not prevent Javier and Malika in [AH3] Accounting from spinning up a plethora of phone-based data-analytics apps, it would prove great for the organization’s momentum and creativity.

That was well before the emergence of AI and machine learning into the broader marketplace, of course. The next generation of AI-powered tools will automate complex technical tasks in ways we simply could not envision just a few years ago. Imagine cloud-based AI products that can streamline everything from data analysis to targeted marketing campaigns to app creation, all with intuitive interfaces that require minimal coding or technical knowledge. In theory, Javier and Malika in [AH4] Accounting can use a no- or low-code tool to create a powerful data-analytics tool with robust AI features for internal use, all via a simple prompt.

By allowing employees to perform tasks previously reserved for tech professionals, companies can unlock a wealth of untapped potential; your folks in Accounting or Marketing or Customer Success or Sales know a lot more about what they need than a software developer on your Product team.

The (Cautious) Rise of Tech-Empowered Employees

But every leader knows that there is sometimes a thin line between creativity and outright chaos. You want your newly empowered employees to use AI to build what they need, but you do not want your company’s tech stack to lose its cohesion. Moreover, your cybersecurity experts and other tech professionals still need to maintain their visibility into the stack for security and compliance (among other mission-critical tasks).

Before non-technical employees utilize AI-powered development platforms to create custom applications or workflows, your organization needs to create a broader strategy for its use of AI. Your leaders also need to level-set their expectations on employees’ use of AI... and set clearly defined limits. Here are some additional elements to consider on this journey:

Assess Current Tech Stack and Identify Gaps: Identify any potential limitations or challenges that may need to be addressed to ensure seamless integration between your existing tech stack and AI development tools.

Develop a Clear AI Strategy: Define your company's objectives for using AI-powered app development, including specific use cases, goals, and resources. Make sure that everyone in the organization is aware of this strategy and its implications.

Establish Guidelines and Policies: Create guidelines and policies to govern the use of AI-powered development tools. Your employees should be aware of the privacy and security implications, for instance.

Provide Training and Support: Offer comprehensive training programs to equip employees with the skills and knowledge needed to effectively use AI-powered development tools. Provide ongoing support to address questions and troubleshoot issues.

Implement Robust Security Measures: Protect sensitive data and prevent unauthorized access. Your tech teams should implement strong security controls, regularly update software, and monitor for potential threats.

If this plan is enacted correctly, these AI tools will empower businesses to harness the collective creativity and problem-solving skills of their entire workforce. Instead of relying solely on a small team of tech professionals, companies can tap into the innovation and expertise of employees across the organization.

The Impact on Tech Professionals

Do AI-enhanced employees threaten the current jobs of tech professionals? While tech pros might have some concerns, it is important to recognize the opportunities in this change in thinking. As AI tools become more sophisticated, more employees will be able to handle everyday tech work, freeing tech professionals to focus on higher-level tasks such as updating the tech stack, training new AI models, and dealing with “edge cases” in cybersecurity and other arenas.

In fact, the rise of these tools may create new tech roles and career paths. For example, some tech professionals could evolve into “AI trainers” tasked with helping employees in their use of AI tools. Other tech pros might find themselves tasked with monitoring and optimizing AI outputs, including those new apps and services.

There’s also the compensation question. Consulting firm PwC recently found that AI-related roles in the U.S. enjoyed a 25% pay premium on average; accountants, financial analysts, sales and marketing managers, lawyers, and database designers and administrators all enjoyed significant pay bumps in exchange for having significant AI skills.

A New Era of Business Models

The AI-driven democratization of tools may also drive a broader change in the way businesses operate. As more employees become empowered to build and iterate, companies can explore new business models and revenue streams. For example, a marketing team could rely on AI to quickly spin up highly customized campaigns in response to news cycles or customer interactions. Manufacturing companies could use AI to streamline design processes, bringing products to market even faster.

Additionally, increased access to AI and software development can foster a more agile and responsive business culture. By empowering employees to experiment with recent technologies and develop innovative solutions, companies can adapt more quickly to changing market conditions and customer needs.

A recent study by McKinsey found that AI-driven automation in telecom operations could lead to a 25-30 % reduction in operational costs. This includes automating network planning, IT processes, and support functions, allowing companies to operate more efficiently and quickly. These improvements are becoming critical as telecom operators face growing pressure to roll out new technologies like 5G, maintain network performance, and reduce downtime. 

In this article, we'll look at how Gen AI is transforming two major areas in the telecom industry: optimizing network operations and speeding up IT processes through automation. By using AI-powered solutions, telecom companies can improve network planning, accelerate software development, and reduce technical debt, positioning themselves for future success in a competitive market. 

This move toward AI-driven operations goes beyond just improving efficiency—it's about reshaping how telecom operators manage their entire IT systems, enabling faster service delivery, lowering costs, and boosting customer satisfaction. 

Network Operations Optimization

Telecom networks are growing more complex with the rollout of technologies like 5G and IoT, making efficient network management a critical priority. Gen AI offers telecom companies new ways to optimize network operations, improve capital efficiency, and reduce operational costs. One of the most impactful areas where Gen AI is being deployed is in network mapping and planning, where it can analyze unstructured data, streamline maintenance schedules, and optimize network resource allocation. 

Network Mapping and Planning with Gen AI

Traditional network management relies heavily on manual processes and structured data analysis, which can be time-consuming and prone to human error. Gen AI, however, can process unstructured data such as supplier contracts, technical reports, and network component specifications to provide a comprehensive view of a network’s infrastructure. 

For instance, a European telecom operator used Gen AI to automate its network mapping processes, reducing the time required for network audits and assessments by 40%. By leveraging AI’s ability to analyze vast amounts of unstructured data, the operator was able to more accurately assess compatibility between network components, predict maintenance needs, and identify areas where operational planning could be improved. This level of insight is vital for preventing costly network outages and ensuring optimal performance during peak usage times.

Google has announced a significant leadership reshuffle as it aims to enhance its position in the competitive artificial intelligence landscape.