Integrating AI technologies with low-code or no-code platforms equips citizen developers to build practical and useful applications, but they must also adhere to security and compliance requirements.
AI citizen development in life sciences blazes a trail to rapid innovation, transforms business operations, and gives you a competitive edge in the industry.
By leveraging the collective knowledge and creativity of citizen developers, your organization is primed to optimize workflows and processes, address complex challenges, and adapt to market changes more effectively.
Key Benefits of AI Citizen Development in Life Sciences
Democratizing software development fosters a culture of innovation and empowerment among employees. It also aligns business users and IT so that applications meet specific needs and comply with IT standards and security requirements. These benefits further help your organization to:
- Reduce costs and increase operational efficiency. By decreasing or eliminating the need for outsourced or specialized staff, citizen developers reduce IT expenses.
- Eliminate manual processes. Deploying automated solutions helps to optimize workflows, purge error-prone manual processes, and minimize potential errors.
- Encourage continuous learning and skills development. Providing opportunities for citizen developers to improve their technical skills contributes to job satisfaction and a culture of lifelong learning and continuous improvement.
Technological and Procedural Strategies for Implementing AI
Innovation is at the heart of AI citizen development, but there are a lot of moving parts in a successful program. Thorough testing and validation help you prevent data breaches, unauthorized access, and other security concerns. Detailed records of your development processes, testing results, compliance maturity, and user feedback facilitate continuous improvement. Regular reviews ensure that you update Standard Operating Procedures (SOPs), Work Instructions (WIs), and governance frameworks to reflect changes in technology, regulations, and business objectives.
The following topics are important considerations for AI citizen development in life sciences.
Security: Vulnerabilities, Threats, and Risks
If citizen developers don’t follow established policies, their applications might enable bad actors to gain unauthorized access to sensitive data or systems. Faulty coding practices often introduce malware into applications and compromise your organization’s system security.
Measures to reduce cybersecurity risk in your organization include:
- Assessing your existing environment. Identify the technologies that safeguard your IT infrastructure and verify individual access privileges. Keep in mind that cybersecurity assessments are not isolated events; the number of applications, devices, users, and endpoints change frequently.
- Mitigating system vulnerabilities. Apply the necessary patches and updates, ensure the operational readiness of backup and disaster recovery solutions, and craft improvement plans that define investment priorities, schedules, and budgets.
- Prioritizing human factors. Accept that human behavior is unpredictable and it’s impossible to fully prepare for unintentional mistakes or intentional misconduct. Best practices include establishing security policies and training employees to heighten their awareness of security threats and risks.
- Monitoring activity. Restrict cybercriminal access to valuable information by proactively monitoring network activity, identifying potential issues, and responding quickly during an attack.
Regulatory Compliance
While citizen developers have the creativity and ability to build useful applications, they may not understand compliance requirements for the life sciences industry, including the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), both of which apply to all organizations that process personal data. Failure to comply with these regulations could result in significant fines and legal liabilities.
Adherence to regulatory requirements includes:
- Developing and implementing SOPs and WIs.
- Establishing standards for data management, security, and compliance.
- Incorporating Application Lifecycle Management (ALM) and Validation Lifecycle Management (VLM) processes that ensure applications meet user needs and comply with industry regulations.
Risk Management
Risk management in life sciences is a comprehensive approach to identify, assess, and mitigate risks throughout an organization. It cannot be an afterthought; it must be built into the development of AI initiatives to best protect you from compliance issues, reputational damage, and financial loss.
To ensure that your AI initiatives comply with established security and compliance standards:
- Identify potential security vulnerabilities and compliance issues associated with AI applications.
- Implement risk assessment strategies to prioritize risks and allocate appropriate resources.
- Develop mitigation strategies that include regular audits, reviews, and IT oversight.
- Maintain continuous monitoring and reporting to verify that your mitigation strategies are effective.
Governance
While citizen development has numerous benefits, it also introduces risks like security vulnerabilities and lack of standardization. A governance framework mitigates these risks by establishing clear guidelines, roles, and responsibilities. In addition to regular reviews, training and IT oversight are essential components for compliance and quality control.
For effective governance and oversight of AI citizen development:
- Create processes and policies specifically designed for AI application development and deployment.
- Incorporate AI governance with your IT governance framework to align AI initiatives with business goals and compliance requirements.
- Use a RACI matrix to clarify who is responsible, accountable, consulted, and informed for various tasks in your AI initiatives (i.e., citizen developers, IT, and management).
Training and Support
To help citizen developers navigate low-code and no-code platforms, provide them with proper training and support. Encourage employees to stay up to date on AI technologies, security practices, and regulatory changes. Give them the information they need regarding:
- Company policies
- Data management
- Regulatory requirements
- Coding standards and practices
- Tools like Microsoft Power Platform, Azure, and Office 365
Plan Your Approach to AI Citizen Development
AI citizen development epitomizes empowerment, transformation, and innovation. By enabling non-technical employees to participate in AI development, your organization will capture diverse perspectives and domain expertise that lead to robust and relevant solutions.
Moreover, AI citizen development promotes a culture where employees are encouraged to experiment, iterate, and continuously improve their AI applications and ultimately drive efficiency and effectiveness.
Designed to automate and streamline GxP-compliant digital workflows, ProcessX is a cutting-edge platform built on ServiceNow. It empowers citizen developers to create, customize, and deploy compliant workflows.
The ProcessX platform offers:
- An intuitive interface. Drag-and-drop design elements enable users to build complex workflows that are tailored to their needs and meet compliance requirements.
- Pre-validated templates. As a starting point for common GxP workflows, the templates ensure that workflows adhere to industry best practices and regulatory standards.
- Continuous validation. Changes made to workflows by citizen developers are automatically validated against predefined criteria.
- A collaborative environment. Built-in communication tools facilitate knowledge sharing and feedback loops amongst citizen developers and IT professionals.
Put the collective expertise of your workforce to work with ProcessX and a citizen development program that considers the security and compliance needs of your life sciences organization. Contact us today to get started.
