Unleash the power of Generative AI with Salesforce

I love the quote by Antoine de Saint-Exupery “A goal without a plan is just a wish”. The success of every project is based on a solid view of why, what and how to change the current situation. Salesforce implementation projects are no exception. Since the recent progress of Generative AI (GenAI), a relevant question has evolved about whether we should reimagine how we plan and run projects. Or at least think about how to increase the efficiency and quality of projects using new AI solutions such as ChatGPT.

The launch of Chat GPT in November 2022 forced many of us to challenge our perspective on the use of AI. ChatGPT made GenAI interesting for a big audience and a topic that companies cannot ignore any more. Unlike traditional AI, which is primarily designed for specific tasks and follows predetermined rules, GenAI is capable of creative output and can produce content that closely resembles human-generated data.

As a digital platform, Salesforce provides technical capabilities to utilise the power of GenAI. It has unique solutions like AI Cloud to deliver AI-created content across every sales, service, marketing, commerce, and IT interaction. In this blog, however, I am not covering aspects of the digital tool itself. I intend to provide ideas and considerations for the project planning and execution. I will walk you through the critical success pillars of Salesforce implementations and highlight the possible changes or improvements that the use of GenAI might bring to those.

Based on the experience of hundreds of implementations, the success of any Salesforce project relies on the following four elements: 1. digital vision and roadmap for the future, 2. ownership and robust development governance, 3. systematic ways of working, and 4. strong user and customer adoption.

These four pillars are the foundation for achieving project goals and ensuring a smooth and effective implementation. Let’s see how we could embed GenAI into these elements.

1. Create a digital vision and roadmap for the future

The first pillar refers to the importance of setting up clear objectives and scope for the project aligned with business strategy and targeted value. People need to see the future vision and path to get there. Having well-defined project objectives and limitations also helps avoid scope creep and ensures that the project stays focused on its intended outcomes.

As setting up the vision and planning the future roadmap requires a sharp view of the situation, different factors influencing the path forward and evaluation of possible outcomes, the capabilities of GenAI can improve the quality of these actions. AI-powered simulations can help explore different scenarios and their potential outcomes, enabling better decision-making both at the strategic level as defining the objectives and in fast ad hoc situations during the implementation. It is also possible to build AI-powered decision support systems to analyse complex data sets and recommend optimal strategies or solutions during the implementation.

Many Salesforce projects aim to improve processes related to customer relationship management. AI algorithms can analyse data and identify process bottlenecks to identify process inefficiencies and enable future optimisation, leading to improved requirement gathering and analysis. With more insight-based project backlog and user story creation, allocating the project resources in the best possible way is easier.

2. Enforce ownership and build robust development governance

Involving all relevant stakeholders from the beginning fosters a sense of ownership and commitment to the project’s success. Lack of ownership is the most typical pitfall and reason for CRM project failure. Equally important is to have a qualified and empowered project team in place. Empowering the team with the necessary authority and resources allows them to make decisions and take action promptly.

Effective communication and collaboration with stakeholders is essential to project governance. Communication helps address concerns, manage expectations, make decisions and gain support during implementation. Here I also see GenAI providing compelling assistance, e.g. automating documentation, creating a knowledge base and answering FAQs, in real-time language translation and generating reports and project insights.

By leveraging GenAI in these ways, project teams can foster knowledge sharing, improve collaboration, and make better-informed decisions. However, it is essential to ensure that the AI-generated content is accurate, relevant, and reliable, and human oversight is still necessary to validate and curate the generated knowledge effectively.

3. Set up systematic development and project management practices

Systematic project management means identifying tasks, allocating resources, setting timelines, and establishing robust and efficient ways of working. Project management can never be fully automated as human interaction is crucial to team engagement. However, GenAI models can help in many ways, e.g., predicting potential risks, allocating resources, and planning timelines. This can be done by analysing historical project data, planned resources and project requirements to optimise actions and forecast possible challenges.

AI-generated designs and prototypes can speed up the development process during the actual implementation, allowing teams to explore different options and iterations more efficiently. Using GenAI makes it easier to explain ideas to different user groups and collect feedback during the early phases of the project, thus avoiding misunderstandings and wrong assumptions related to solution requirements. In addition to prototyping, GenAIcan assist in automating code generation, accelerating development and reducing the risk of errors. The use of GenAI in software development and coding is a topic that deserves special attention, and many more blogs must be written to cover the theme.

The testing approach is one of the most crucial elements in systematic development practices. Rigorous testing and quality assurance processes are essential to project success, as addressing any issues before full deployment minimises disruptions. GenAI can aid in identifying errors or anomalies in large datasets or complex systems, expediting the debugging process. AI-generated test cases and automated quality assurance techniques can significantly reduce the time and effort required for testing, ensuring a more robust implementation.

Establishing performance metrics that allow the project team to monitor progress and evaluate success is also important. Regular assessments help identify areas for improvement and potential adjustments. With the help of GenAI, project managers can monitor performance continuously and make timely adjustments as needed. GenAI can automate the tracking of KPIs and generate performance reports and recommendations for actions. It can compare project performance against industry benchmarks or historical project data and provide valuable context for performance evaluation, trends and patterns.

4. Emphasise user and customer adoption

Salesforce implementation should never be seen only as a technical exercise but as a project that changes human interactions and working methods. Thus, the success of the implementation depends on the customer and user adoption level. Acknowledging and addressing the impact of change on different stakeholder groups and processes is essential. A structured change management approach helps manage resistance, supports adoption, and ensures a smooth transition.

There are several ways to drive user adoption. And many feasible options to leverage GenAI capabilities as part of the adoption process, e.g. to enhance communication, make informed decisions, and foster a culture of adaptability. In the project’s early phase, GenAI can provide insights to support creating a change strategy and identify change impact. For example, AI algorithms can assess the potential impact of changes on different aspects such as processes, resources, and customer experiences. In the same way, readiness can be assessed using GenAI to help identify areas that require special attention during the project.

Training can be supported by GenAI recommending personalised materials and development programs for employees to acquire the necessary skills and knowledge to adapt to the changes. Additionally, GenAI solutions can be built to support many different learning approaches. We have seen concrete examples already where learning assistance is provided with different methods:

• Adaptive learning (approach to adapt the content, pace, and difficulty level of educational materials based on the learner’s performance and progress)
• Socrative Learning (solution acts as a facilitator, guiding students through a series of thought-provoking questions and discussions rather than simply delivering information in a lecture-style format)
• Analogy Learning (learners draw similarities between the familiar concepts they already understand and the new or unfamiliar concepts they encounter)
• Active Recall based learning (information is repeated or tested in intervals based on individual performance, e.g. in flashcards or enforcing note taking or teaching others)
• Storytelling approach (technique that involves using narratives, anecdotes, visualisations or stories to convey information, concepts, or knowledge to learners).

Analysing the impact and following feedback closely is crucial to enable organisational learning and growth. AI tools can continuously monitor change progress and collect stakeholder feedback for change management. Close feedback loops allow project teams to make iterative improvements and address emerging issues. GenAI can also analyse historical data and communication patterns to detect signs of change resistance. With the help of GenAI, it is possible to assess the effectiveness of change initiatives and measure their impact on key performance indicators. This evaluation provides valuable insights for future change efforts.

5. Future of implementation projects

Overall, the integration of generative AI in implementation projects can lead to increased efficiency, better decision-making, enhanced user experiences, and improved project success. I have only covered a small sample of possibilities in this blog and assure you that even in the near future, we will see many use cases that are hard to imagine today. Or, as ChatGPT visions the future in a very poetic way:

“Embracing GenAI in project management opens new horizons for success. It optimizes resource allocation, fosters creativity, and enables agile decision-making. With the ability to analyze vast data and generate context-aware responses, GenAI becomes an indispensable ally for efficiency and adaptability. Let GenAI be our guiding light on the journey to project success, propelling us into a future of limitless possibilities. Together, we shape today’s projects and lay the foundation for tomorrow’s, elevating implementations to new heights”