According to the Harvard Business Review, a massive $48 trillion are invested in projects, yet the Standish Group cites that only 35% of projects are considered successful .
“The wasted resources and unrealized benefits of the other 65% are mind-blowing,” says Antonio Nieto-Rodriguez and Ricardo Viana Vargas, from the Harvard Business Review. Clearly, there is a huge opportunity for the success of projects to better reflect the talent and work that gets poured into them.
Imagine Lisa, a Project Manager at a mid-sized company. Lisa is managing the launch of a new product line for her company, which involves coordinating multiple teams, including research and development, marketing, sales, and customer support. Each team has its own set of tasks and deadlines, which are highly interdependent. For instance, the R&D team needs to finalize the product design before marketing can create promotional materials, and sales training sessions can’t happen until the product features are fully understood.
The project also requires integrating feedback from a beta testing phase, requiring timely communication between the development team and beta users. Additionally, Lisa needs to ensure that all the necessary regulatory approvals are obtained, which involves coordinating with legal and compliance teams.
Without AI, Lisa manually schedules tasks, tracks progress, and reallocates resources, often discovering bottlenecks only after they become critical issues. She spends a significant amount of time in meetings trying to align the different teams and update project plans. Communication breakdowns are common, leading to misunderstandings about deadlines and task dependencies. Decision-making is slow, as Lisa lacks real-time data and insights, which can delay the launch and impact the project’s success.
Clearly, Lisa would benefit from a tool providing automation and insights for Project Managers.
The right AI Project Management tool will depend on the needs of your team and your organization. To get started, you can ask yourself a few basic questions:
As AI popularity grows, so do best practices. While it’s clear that the full potential of AI in Project Management is still being explored, it’s becoming increasingly common to have dedicated councils overseeing AI usage. This evolving framework aims to balance innovation with safety and reliability, setting a solid foundation for the future of AI-powered Project Management tools.
Even without a dedicated council, your organization can take smart steps to ensure positive implementation of AI tools. Lareina Yee, a senior partner with McKinsey, says that responsible AI needs to “start at day one.” This means that teams are well versed in the risks of AI and mitigation of said risks, with early and consistent testing along the way.
Commonly reported risks, according to recent McKinsey survey , include privacy bias, intellectual property infringement, and security concerns. In order to mitigate these risks, McKinsey recommends the practice coined “shift left,” meaning shift reviews and testing of AI tools as early as possible to mitigate cybersecurity risks and prevent inaccuracies.
One thing to remember as you get started is that machine learning systems need to be fed data. So don’t rely on the same public information everyone else has access to through the platform. Instead, learn how to feed AI unique data so it can better serve your goals.
Don’t fall into these 5 common pitfalls when embarking on your AI journey:
Will ai replace project managers.
Fear not, Project Managers! AI is not here to replace you. Rather, these tools of the future can free your teams to spend less time on manual tasks, and more time focusing on creative problem-solving, strategic planning, and achieving project goals.
For more project success using AI, ask questions like: What do I need more visibility into? What financial forecasting would be helpful? What past projects can serve as templates? AI-powered solutions are hungry for data and the more you feed them, the more they can help you be better Project Managers.
While AI can automate time consuming work, it cannot replicate the human touch needed for strategic thinking, leadership, and team collaboration. Project Managers will still be essential for setting project vision, making complex decisions, and navigating interpersonal dynamics within teams. Instead of replacing Project Managers, tools like OnePlan empower them to focus on higher-level responsibilities, improving efficiency, and ultimately leading to greater creativity and time for strategic initiatives.
“AI offers an opportunity to free up Project Manager time and allow them to do what they do best—lead teams and get the very best out of people. This will no doubt deliver far better results, fewer errors, more motivation, and greater success,” says Peter Taylor, Vice President of Global Project Management at Ceridian and author of AI and the Project Manager: How the Rise of Artificial Intelligence Will Change Your World.
Chat GPT has been around for over a year now. If you’re not benefiting from this resource, it’s time to start! AI Project Management tools like ChatGPT don’t have to be daunting. If you’re not sure where to start, take a look at these 15 prompts Forbes put together for Project Managers. Here are a few complex tasks that ChatGPT can help with:
1. Task Management and Scheduling
2. Communication and Collaboration
3. Documentation and Reporting
4 . Resource Management
5. Risk Management
6 . Decision Support
7. Training and Onboarding
8. Knowledge Management
9. Integration with Tools
10. AI-Driven Insights
To better communicate with your team and stakeholders as a Project Manager, you can use ChatGPT to:
By integrating ChatGPT with their existing workflows, Project Managers can save time, enhance accuracy, and focus more on strategic tasks. In fact, some systems may even have built-in AI-powered GPT assistants where you can ask ask for reports and insights from internal company data.
While other Project Management tools may automate complex tasks within teams, OnePlan goes the extra mile with visibility and insights into the entire enterprise, making it the ultimate AI-powered project software.
It’s like having the ultimate co-pilot by your side. The best part? This co-pilot tackles the tedious tasks and offers valuable guidance, making your team more focused and effective.
AI tools are revolutionizing Project Management by automating routine tasks, predicting potential problems, and improving team communication. By generating real-time updates, forecasting risks, and providing instant support, AI allows Project Managers to focus on strategic decisions and creative solutions. By reducing mistakes and boosting efficiency, these tools allow people to dedicate more time to the work that matters and let automation take on the busywork.
It might feel like AI burst onto the scene overnight, but it’s been two years since ChatGPT came out and even more since automation tools began to transform the potential for smarter work habits. Do more than just “keep up,” with this trend in the digital landscape of Project Management. Use it to your benefit and deliver your best work yet.
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Eppo lands new cash to grow its app, website and ai experimentation business.
The AI industry continues to release tons of new models, and companies looking to stay competitive are racing to adopt them for their purposes. In fact, nearly 10% of businesses plan to spend a whopping $25 million this year on AI initiatives , according to tech consulting firm Searce.
But while lots of money is being spent on AI, it's unclear the ROI is there. Half of all AI leaders aren't sure how to calculate or demonstrate the value of AI projects , according to Gartner.
Ex-Airbnb data scientist Chetan Sharma makes the case that figuring out AI ROI is no heavy lift with the right tooling. Sharma is the co-founder of Eppo , an experimentation platform that lets customers evaluate and customize AI models for specific use cases. Beyond its model evaluation suite, Eppo provides a general A/B testing platform and service for apps and websites.
"With new AI models launching weekly and companies pouring millions into them, A/B testing offers a cost-effective way to evaluate their effectiveness without overspending," Sharma told TechCrunch. "Eppo helps companies identify which models truly deliver value and enables smarter, more sustainable decisions in an environment of rapid innovation and escalating costs."
Eppo competes with a number of experimentation and A/B testing startups in the market, including Split , Statsig and Optimizely . Big tech giants like AWS, Microsoft Azure and Google Cloud also offer a growing number of model fine-tuning and evaluation tools.
But Sharma says that Eppo stands apart from the crowd thanks to features like its "contextual bandit" system, which automatically spots new variants of customers' websites, apps or AI models and actively explores the performance of those variants by serving increasing load or traffic to them.
"Experimentation drives velocity and accelerates growth by stripping away bureaucratic — and often incorrect — decisions by committee while tightly tethering initiatives to growth metrics, killing bad ideas fast while canonizing good ideas for reinvestment," Sharma said. "Eppo’s approach to live 'online-eval' tests of AI models answers whether premium models improve metrics."
Eppo, which launched out of stealth in 2022 , now has "several hundred" enterprise customers in its roster, including Twitch, SurveyMonkey, DraftKings, Coinbase, Descript and Perplexity, according to Sharma. Alexis Weill, Perplexity's head of data, told TechCrunch that Eppo has allowed Perplexity to "significantly scale" the number of experiments it runs concurrently.
Investors seem pleased. This week, Eppo closed a $28 million Series B round led by Innovation Endeavors with participation from Icon Ventures, Amplify Partners and Menlo Ventures. Sharma says that the new cash, which values Eppo at $138 million post-money and brings its total raised to $47.5 million, will be put toward bolstering Eppo's marketing and AI experimentation capabilities, enhancing its analytics offerings and scaling its go-to-market efforts.
San Francisco-based Eppo currently has 45 employees and expects to end the year with 65.
"The demands of efficient growth along with the rise of AI has combined to an adapt-or-die mentality that forces companies to become experimental," Sharma said. "And due to the gaps of legacy vendors, most of the experimentation market had chosen to staff large in-house teams and build over buy. With so much employee movement and layoffs, these in-house teams are no longer sustainable, leading to companies seeking out Eppo to replace expensive or orphaned in-house builds."
This article originally appeared on TechCrunch at https://techcrunch.com/2024/08/20/eppo-lands-new-cash-to-grow-its-app-website-and-ai-experimentation-business/
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