Your readiness rating for development democratization and growth: BeginnerIntermediateAdvanced

Readiness rating: Low

Your score indicates that your organization is minimally prepared to enable development growth through the use of genAI-infused development tools and low-code. This is similar to 32% of IT leaders surveyed.

Our study shows that there is a strong correlation between low-code maturity and genAI readiness. The use of low-code and genAI development tools, such as AI agents, can accelerate development efforts, but this growth may unintentionally amplify existing gaps with data, security, and governance. It’s important to address those issues before committing to a development democratization strategy for accelerating development work.

Low-code recommendations:

For organizations with a low level of readiness, the focus should be on setting a strategy that encourages and enables low-code use among both professional and citizen developers.

• Establish a more proactive citizen development strategy. Recognize and support citizen developers as a new category of IT customers, providing them with the necessary tools and training. Promote low-code platform adoption to enable citizen developers with development opportunities.
• Move away from delivery silos. Align low-code experts within business functions to promote upskilling and enablement of fusion development teams (i.e., pro and citizen developers). Focus on early adopters to identify local champions.
• Establish clear governance policies. Develop and refine governance policies to manage risks associated with citizen development (e.g., data security, compliance, financial loss) while accepting some level of waste and ambiguous ROI in the short term.
• Be open to using low-code for core applications. Explore options for low-code development for important or critical business applications. Our survey found that only 26% of low-readiness companies are using low-code development for core/critical business applications — 30% less than high-readiness organizations.

GenAI recommendations:

As you gain a more grounded knowledge of genAI and potential use cases for development, focus next on enhancing existing processes and expanding genAI capabilities.

• Data governance. Implement processes to monitor and govern data used in genAI models to ensure data integrity and reduce the likelihood of false outputs.
• Guidelines for genAI use in development work. Create clear guidelines for appropriate genAI use cases, including safeguards, such as human reviews, prior to publishing any genAI-driven outputs, such as AI agents.
• Foundational training. Train all employees on how genAI works, covering topics like data sources, data models, natural language processing, and AI agents to improve competence and reduce potential risks of errors.

Readiness rating: Medium

Your score indicates that you organization moderately prepared to enable development growth through the use of genAI-infused development tools and low-code. This is similar to 45% of IT leaders surveyed.

Our study shows that there is a strong correlation between low-code maturity and genAI readiness. The use of low-code and genAI tools, such as AI agents, can accelerate development efforts, but this growth relies on having the right data, security, and governance processes in place. Establishing and maintaining proper data access controls and monitoring will enable faster growth in development work

Low-code recommendations:

For organizations with a medium level of readiness, the focus should be on scaling and optimizing low-code adoption.

• Expand the recognition and enablement of citizen developers. Integrate citizen developers into the IT customer base, recognizing their growing importance and contributions. Increase efforts to enable and build skills across business functions by integrating low-code tools across more departments and workflows.
• Improve training and mentoring. Provide advanced training and mentoring programs for both IT and citizen developers to improve technical and process skills. This includes more deliberate pairing of pro and citizen developers on high-value projects.
• Refine risk management policies. Develop more nuanced risk management policies that balance speed, agility, and risk, allowing for some level of experimentation and innovation. Establish a center of excellence — inside or outside of IT — with a focus on training, adoption, and governance.
• Strategic application development. Encourage the use of low-code tools to deliver on both modest and complex solution delivery, leveraging data insights to identify high-impact use cases. Begin to assess application portfolio for modernization opportunities and identify software-as-a-service (SaaS) apps to retire and consolidate onto the platform. Start by focusing on niche create, read, update, and delete (CRUD) apps.

GenAI recommendations:

As you gain a more grounded knowledge of genAI and potential use cases for development, focus next on enhancing existing processes and expanding genAI capabilities.

• Advanced data governance. Implement more sophisticated data monitoring and governance frameworks to ensure high data quality and integrity.
• Guidelines and safeguards. Develop detailed guidelines for genAI use, including advanced safeguards, such as automated checks and balances, in addition to human reviews.
• Expanded training. Offer specialized training programs that go beyond the basics, covering advanced genAI functionalities, autonomous AI agents, ethical considerations, and best practices for integrating genAI into development workflows.

Readiness rating: High

Your score indicates that you organization is highly prepared to enable development growth through the use of genAI-infused development tools and low-code. This is similar to 22% of IT leaders surveyed.

Our study shows that there is a strong correlation between low-code maturity and genAI readiness. The use of low-code and genAI tools, such as AI agents, can accelerate development efforts, but it’s important to ensure that proper data, security, and governance measures are maintained. Effective monitoring and management of data will reduce complications as the volume of development work increases via democratization.

Low-code recommendations:

For organizations with a high level of readiness, the emphasis should be on driving innovation and achieving strategic business goals through low-code development.

• Empower citizen developers. Recognize non-IT developers as primary or coequal contributions to application development, providing them with the support and resources needed to succeed. Recognize citizen development as a standard business skill and make curated/governed data and services available companywide.
• Comprehensive tool deployment. Ensure low-code tools are deeply embedded in the organization’s software development lifecycle, with widespread access and usage. Mandate “low-code first” for new dev projects (i.e., must try low-code platform before writing new pro-code). Begin to strip away large software-as-a-service (SaaS) application modules (looking for consolidation opportunities) and focus on processes unrelated to legal/compliance requirements (e.g., business operations such as sales).
• Strengthen security and governance processes. Focus on platform security, compliance, and governance to enable speed, autonomy, innovation, and agility. Implement advanced governance frameworks and compliance measures to manage data access and integrity effectively. Embrace a security-first mindset development for citizen and pro developers.
• Cultivate a culture of continuous improvement. Foster a culture that values both deep technical expertise and pragmatic citizen development delivery, focusing on continuous upskilling and innovation. Focus on building a community of champions, mentors, and practitioners that can support their individual business practice areas.

GenAI recommendations:

With a solid understanding of genAI and its value, next focus on maximizing the strategic impact of genAI development tools to foster a culture of continuous innovation and optimization.

• Proactive data management. Establish proactive data management strategies to preemptively address potential issues.
• Comprehensive governance. Create comprehensive governance frameworks that encompass all aspects of genAI use for development, from data sourcing to output validation, to ensuring compliance.
• Continuous learning and innovation. Promote a culture of continuous learning and innovation by providing ongoing training opportunities, encouraging experimentation with genAI-infused development tools, and fostering cross-functional collaboration to drive genAI adoption and innovation. Champion successful genAI use cases, such as AI agents, that are driving business value.