The AI Project Management Gap – 5 Tools Separating Top Performers From the Rest

AI in project management refers to the use of artificial intelligence and machine learning capabilities to help with various task management processes. This includes progress tracking, scheduling, status updates, and workflow automation — teams can leverage AI to help with these tasks more efficiently.

Using AI in project management, you’ll improve efficiency while reducing human errors. You’ll also benefit from the ability to make data-driven decisions that ultimately boost project success rates.

Let’s explore how you can use AI to transform project management processes by looking at its benefits, applications, and key use cases.

AI helps managers handle complex projects and derive takeaways from their projects more easily so they can make smarter decisions. That said, here are five examples of real-world use cases that you could consider using.

Imagine you’re a project manager at a Sydney-based software development firm using a machine learning model to analyse past release cycles.

Predictive scheduling models can be used to forecast and make predictions. They’ll update their logic based on whether your last sprint failed or succeeded and then send the info back to you so you can forecast more accurate timelines for feature releases going forward.

You can respond rapidly to blips because the ML model will proactively notify you of problems. This approach (courtesy of AI’s forecasting capabilities) can help you avoid missed launch dates.

Imagine an e-commerce retailer in Melbourne that employs AI to automatically create and assign tasks. They’ll also need to regularly update the tasks as they progress (which the AI can handle easily).

When orders rise during holiday sales, an AI automation tool diverts resources to the busiest teams when orders rise during holiday sales. It also sends reminders if tasks are nearing their due dates. Doing so helps everyone stay on track.

This frees managers to focus on strategy instead of routine and irritating check-ins (for both managers and team members). The automated notification serves as an impersonal, helpful reminder.

A Queensland-based construction company might leverage AI to spot red flags in massive building projects. Using intelligent risk management, it can take an objective view of what it’s analysing at speed and scale and will simply outperform the human brain at spotting flaws.

In the construction industry, this can mean identifying a problem in a building project that an overworked project manager with a lot on their plate might have missed — which can have huge positive ramifications for spotting simple mistakes that could end up being quite costly.

The AI tool could then highlight early signs of overspending by analysing progress reports as well as budgets and resource allocations. It may also identify a key backlog with a specific project task that could lead to schedule slippage.

Today, many managers are thankful to rely on AI as a failsafe as it can adjust timelines or shift resources to handle the issue before it escalates. This example of AI as a failsafe really showcases the synergies of AI and humans working together to manage risk management better.

A Brisbane consulting agency could use AI-driven NLP to develop meeting agendas and draft follow-up emails after client workshops.

Generative AI is used in this way is a significant upgrade that cuts down on tedious admin time, letting consultants dive into problem-solving rather than recapping every session by hand.

It’s a simple, time-efficient way to share information (though it’s important to remember everybody still has to read the notes for them to be worthwhile).

Let’s consider a Perth-based mining services firm using AI-enabled dashboards that pull data from multiple sites across Western Australia.

Project updates, supply chain info, and budget changes populate instantly — ensuring every stakeholder sees the latest status.

This real-time visibility ensures that everybody who has access can check in on these figures and get updates in real-time, which reduces the need for lengthy, cumbersome email threads. Furthermore, this data could also be connected to Slack to create a seamless collaboration experience.

These hypotheticals clearly show how you can use AI to elevate efficiency in your projects. They ultimately work alongside your human strengths and business acumen for smoother project completion and stronger results.

There are a number of ways you can use AI in Salesforce to help you get the most out of your projects. Here are 5 ways AI can help improve your project outcomes.

Salesforce AI helps you get the most out of your team while making sure they don’t experience burnout. You can use its AI to assign tasks, like client onboarding or prospect check-ins, to team members based on their skills and availability. There are also reminders that will help team members stay accountable for their tasks.

On top of this, Salesforce AI can analyse your resourcing plan and suggest ways to improve your workflow, and identify any potential bottlenecks before they affect your deadlines.

For example, Syndex used Salesforce to automate workflows and reporting and now spends 50% less admin time on their projects to unlock growth opportunities.

Imagine if you could see when your project was heading to disaster and do something about it before it strikes. With predictive risk management, you can!

The AI does this by analysing past project data and looking at your resource plan to forecast if you are going to go over budget or do not have enough resources to finish the project successfully.

Salesforce AI goes a step further than other tools on the market by using communication data from your emails, video transcripts, chats, and reports to predict your project health and team morale. It uses this data to notify you in advance and help your business increase productivity, and, at the same time, reduce risk.

As any project manager will tell you, balancing your project budget requires a delicate balance. If you are working on for-profit projects, you’ll want to ensure you are bringing in more revenue than the costs of resources coming out.

Salesforce AI uses expense forecasting, real-time costs, and historical data to predict what your expenses will be and if you are going to blow your budget. Knowing this in advance means you can make changes before they go over budget.

In fact, using Salesforce Artificial Intelligence, Living Edge was able to reduce its costs by 82% in just the first month by gaining a better understanding of its project profitability.

Taking notes can pull you out of being present in your meetings. Salesforce AI works as an AI personal assistant for all your meetings. For example, if you are on a video call with your client, the AI can note down all the client questions you said you’d get back to them on so you can follow up with ease.

You can also use our AI as a chatbot to ask key questions about your project. The AI will then search through all its data to provide you with an answer. This is great for both understanding where your project stands and providing clear answers to client questions.

Using Salesforce AI, Community Vision was able to lower its customer call volumes by 30% by providing customers with the right information at the right time.

Gathering reports for all your stakeholders can be a major time-suck. Salesforce AI can do the job for you by gathering all your data into detailed yet clear reports.

You can identify your KPIs, and the AI will identify their trends and recommend improvements you can make to meet your goals.

For project teams that want to keep track of where their KPIs stand, the AI can also generate custom dashboards that give you a bite-sized view of the most up-to-date metrics.

When businesses apply AI-driven technology within their project management tools, they can benefit in various ways:

You’ll see this as a running theme in any commentary on AI benefits. AI’s predictive, automated analytics simply outperform human analysis in terms of reliability, speed, scale, and insight. AI can spot potential bottlenecks or missed deadlines before they escalate, letting teams plan more confidently.

AI can do a lot of the donkey work of project management with ease. By automating routine tasks (like updating due dates or sending progress notifications), project managers have more time to focus on leadership and strategy. These leadership and strategy decisions often require a more human approach. As such, reducing manual tasks in favour of strategic sessions can be a much better use of your time.

Sometimes, integrating all your data to make the right decisions regarding resource management can be challenging. How can you best use everything at your disposal to benefit the project and the business?

AI can boost this resource allocation. It looks at skill sets, schedules, and historical project data to assign the right people to the right tasks, helping prevent overwork and keep teams happy.

With AI-driven dashboards, everyone can see updates, risks, and changes in real-time — no more waiting for end-of-day status reports from people who may have other tasks to complete (and the project will benefit from them working on those rather than this unnecessary reporting).

While these benefits should be evident to any project manager considering implementing AI in project management, it’s also important to realise that you’ll need to intelligently apply AI to address a problem or increase the efficiency of a process.

Let’s look at some specific ways teams are using AI to help show how you can use AI in your team.

Incorporating AI features can seem intimidating if you’ve never used them before. But the thing is that most AI tools are super intuitive and, as a relatively new technology, are built with an understanding that they should be easy and pain-free to adopt. Here’s a straightforward roadmap for you and your team.

Start by understanding where you could use AI to boost your current workflows. Look for repetitive chores (like status updates) or data-heavy tasks (like budgets). Projects with a track record of historical data are perfect candidates since AI capabilities thrive on past information to deliver new insights for you.

It may sound like an obvious point, but ensure you pick a tool with key features that match your biggest pain points. Are you in need of advanced analytics, an AI assistant to help schedule meetings, or a tool that does both and more? The best choice depends on whether you’re fixing resource bottlenecks or trying to get better at risk detection. Budget may also be a factor as you evaluate the tools available.

You’ll need to convince those with the purse strings, leadership teams, and your team members that investing time and money into the new technology is going to be worth it. It’s helpful to gently introduce the tool and explain how it eases bottlenecks or automates routine tasks. You can also show how it can free up teams to tackle more strategic responsibilities.

It’s vital to understand exactly what determines success for your AI tools and what they bring to your project management processes. Decide on the metrics you’ll track, like how quickly tasks get done or how accurately you forecast budgets. Defined KPIs during the project planning process let you gauge the impact of AI on project success.

Don’t be afraid to test things out by starting out small. Feel free to pilot your new tool on a single project or department within the business; then, you can note what works well and where the system struggles.

It’s important that you then use that feedback to refine your approach before a broader rollout. This can be a great step that also helps to reaffirm the stakeholder buy-in you were trying to create in Step 3.

We suggest delivering how-to sessions or short guides to help teams get up to speed. It’s so important that they understand these new tools can benefit them. Your teams need to feel comfortable not only with the interface but also with the concept of letting AI guide part of their workflow.

Here are some helpful tips and best practices that you can use if you’re looking to use AI in your project management.

• Check your data. AI is only able to make good calls if your data is reliable. The quality of the output is completely dependent on the input, so things like out-of-date customer data will skew your results. Regularly update tasks and resource information.
• Start it slowly. Focus AI efforts on a few key processes (like scheduling) before diving into more ambitious automations. Quick wins build team confidence.
• Monitor and tune as you go. AI isn’t foolproof or a panacea that will automatically fix everything for you. You should keep tabs on how well it handles project outcomes and revise settings or data inputs as needed.
• Keep human judgment. While AI handles the routine, project managers still provide leadership, handle complex decisions, and maintain the team’s morale as you progress toward project delivery.

AI makes managing projects easier. It saves time, and it is more efficient. AI solutions can be applied to the entire product development lifecycle — from planning to final delivery. Tasks can be automated, risks can be anticipated, and project managers gain more visibility over their operations.

Salesforce Artificial Intelligence can provide you with intelligent task automation, predictive analytics, enhanced collaboration, and automated reporting. Plus, a whole lot more. Learn more by watching a demo today or speak with our experts.