10 Ways AI Monitoring Tools Reduce Outsourced Development Risks

The global software development outsourcing industry has reached unprecedented heights, with market revenue set to grow to $591.24 billion over this year. That means businesses do not need to decide if they need to outsource development, but how and where to do it. In fact, outsourcing is already a universal practice among the world's largest corporations, with 92% of G2000 companies using vendors to cut costs and focus resources on strategic business tasks. 

Of course, outsourcing comes with risks as well, such as miscommunications and different approaches to work that lead to delays and extra expenses. Fortunately, the advancement of AI technology allows client-companies to see directly into their outsourcers' work to minimize these disadvantages and unlock the global talent pool for their projects.

AI-monitoring tools: observation without micromanagement

One of the central problems clients encounter when working with outsourcers is a lack of visibility into the project. Businesses hire vendors to create software products and solutions, and stakeholders want to receive regular updates and understand how the project aligns with business goals. Unfortunately, the client-outsourcer relationship can lack the necessary level of transparency. That is where AI-monitoring tools can help both sides of the relationship achieve their goals.

The benefits of AI tools, however, are often overshadowed by the negativity associated with employee monitoring. Large companies have demonstrated how they use technology to monitor employee communications to understand their reaction to policies, as well as feedback, and to identify harassment and bullying. This approach creates mixed reactions among employees and society in general, but it does not have to be the only option in regard to AI monitoring.

Employees and external vendors perform regular actions, such as task status changes, comments to tasks, logging time, writing reports, creating code commits and closing them, and many more. AI tools can monitor these activities to produce insights, updates, and predictions based on regular employee behavior. It is not spying but observation to keep teams on track and clients informed of a project's progress.

10 ways to use AI-monitoring tools

1. Supervise and forecast outsourcing expenses with data-driven precision
   AI tools analyze historical project data to forecast completion timelines, resource requirements, and potential cost overruns before they occur. These systems allow clients to avoid unpleasant invoice surprises because they deliver visibility into real-time expenses and costs.
   
   
2. Maintain development transparency across geographically distributed teams
   AI monitoring systems provide transparent oversight of development progress without intrusive surveillance. These tools track professional task completion, code commits, and milestone achievements to give organizations clear insight into project status.
   
   
3. Eliminate manual report collection from multiple vendor sources
   AI systems automatically compile comprehensive project status reports by aggregating data from multiple development tools and platforms. This eliminates the need for managers to request and collect reports from various vendor teams or "hunt" down the manager with the right information.
   
   
4. Establish performance standards across diverse teams
   These systems establish objective performance criteria through automated data collection and analysis of development velocity, code quality, and delivery timeliness.
   
   
5. Detect project risks before they impact deliverables
   AI algorithms detect subtle patterns that may indicate future project risks or bottlenecks before they become apparent to human managers.
   
   
6. Optimize resource allocation based on productivity data
   Systems monitor professional engineering activities such as code commits, documentation updates, and task completions to provide objective productivity metrics. In turn, this can reduce time to market.
   
   
7. Enforce consistent code quality standards across external teams
   AI tools continuously evaluate code against established quality standards, best practices, and organizational guidelines. Automated alerts keep teams on track to maintaining proper quality.
   
   
8. Prevent deadline slippage with automated reminders and alerts
   AI monitoring platforms track task progression through development workflows and provide automated reminders for approaching deadlines or blockers that require attention. This reduces micromanagement and friction that results from constant human reminders.
   
   
9. Safeguard intellectual property through anomaly detection
   Advanced monitoring identifies unusual patterns that might indicate security vulnerabilities, compliance issues, or policy violations within the development environment.
   
   
10. Streamline oversight without disruption to established workflows
    AI monitoring solutions connect seamlessly with version control systems, issue trackers, and project management platforms to collect data without disrupting established workflows.
    

All of these benefits connect to more transparency in outsourced development projects. When clients understand what is happening, there is a lower chance of conflicts and misunderstandings arising. Likewise, observation does not involve interference in vendor workflows or meetings that occupy valuable time in schedules.

Enji streamlines work with outsourcers

Businesses that hire outsourcers can reap these benefits and other AI features with Enji, a single platform that integrates with client and vendor tools. Enji collects data without disrupting workflows and offers concise text-based reports that keep managers up-to-date on projects. Project visibility is at the heart of the platform and is made possible through various features:

Enji helps clients unlock high productivity in their outsourcing teams and save money. Instead of countless emails and meetings to receive project updates, stakeholders get essential information in minutes, thanks to these features and visual dashboards.

Best practices for monitoring outsourced teams to reduce risks

AI monitoring tools give clients and stakeholders more visibility and data concerning the development process; however, there are best practices that clients need to employ in order to use this information to boost performance and not reduce it.

1. Establish clear expectations at the beginning

AI cannot do everything to create a better outcome in outsourced software development projects. The client also needs to understand what criteria they will use to measure a vendor's performance and the results they demonstrate, and AI monitoring tools are an excellent choice to make. When the criteria are clear and put in writing before any work has begun, it will be easier to implement objective, automated tracking that compares actual work against the expected outcomes.

2. Observe without micromanagement

The ability to observe a project's progress can create the assumption that clients should intervene whenever they notice small issues. Too many interventions can reduce developer productivity. Instead, clients can focus on insights from the tools that outsourcers receive as well and ask questions when they notice critical issues.

3. Create a culture of transparency and continuous improvement

When clients demonstrate a sincere interest in transparency and quality, it will be easier to receive the same from an outsourcing team. The results of AI will only match the input and desires of the clients. Likewise, this encourages better information sharing and will facilitate a smooth transition when the project is complete.

Outsourcing companies share an interest in successful projects and the positive reputation they deliver, and AI monitoring will only increase the chances of such an outcome.

Start transforming your outsourcing

Don't just trust vendors with your software development projects—verify their progress with Enji's powerful AI monitoring tools. Join the forward-thinking businesses that are already maximizing outsourcing ROI through enhanced visibility and data-driven insights.