How is AI impacting your profession?

Many people are concerned about the not-so-positive impacts of AI on their day to day work and potentially their actual careers as a whole. Learning new skills and being across the potential of AI requires an upskilling and growth mindset not everyone is ready for. Yet we find ourselves at the frontier of an AI revolution that promises to redefine the very essence of our work and we have the choice to decide if this will be a positive redefinition or not.  

The pressing question for many ambitious professionals is not if, but how to adapt and future-proof our own careers in the wake of AI's advancement. 

In this post we will begin by taking a look at three particular career streams being impacted by AI -  project management, engineering and C-suite executives  - and how they are leveraging AI. 

Understanding AI's Role in Your Industry

The first step is to demystify AI and its implications for your particular industry. AI, in its essence, is about enhancing decision-making processes, automating routine tasks, and creating opportunities for more complex and creative work. For engineers, among other things, this may mean deepening their expertise in machine learning and robotics, leading to more innovative designs and solutions. Project managers could leverage AI tools to improve resource allocation, risk assessment, and project timelines. Executives might integrate AI strategies into the organisation's business model, ensuring the company stays ahead of the curve. 

Upskilling: Your Protective Gear Against Obsolescence

AI-induced transformation necessitates a learning mindset. Continuous professional development and a growth mindset is the most effective shield against potential obsolescence. 

Engineers should focus on understanding how AI can support system optimisation and predictive maintenance. Learning to work alongside AI/machine learning algorithms will be a priceless skillset.

Artificial Intelligence (AI) offers a broad spectrum of benefits and applications for engineers across various fields, enhancing their capabilities, optimising design processes, and enabling more efficient operations. Here's a few ways AI can assist engineers:

1. Design Optimisation and Automation: AI tools, particularly generative AI, are revolutionising the way engineers approach design tasks. These tools can analyse large datasets to optimise designs for efficiency, cost, and performance, often achieving results that might not be intuitive to human engineers. This allows for the creation of more innovative solutions in areas such as smart factories, autonomous vehicles, and drones with minimal human intervention How AI aids engineers.

2. Quality Assurance and Control: AI and automation technologies significantly improve the processes of quality assurance (QA) and quality control (QC). By automating these processes, engineers can focus more on design and complex problem-solving tasks. AI systems can ensure consistent performance and high-quality outcomes in manufacturing and other engineering fields by learning from engineered data How AI and automation will help engineering and humanity.

3. Enhanced Product Development: In product design and development, AI can expedite and refine the process by handling repetitive and time-consuming tasks, allowing engineers to concentrate on more critical aspects. AI can process multiple use cases to identify and test boundary conditions, integrate designs more seamlessly, and facilitate better communication among collaborators Using AI to speed up and improve product design.

4. Decision Support Systems (DSS): AI-driven decision support systems can manage and supervise engineering processes, providing valuable insights for strategic management. These systems help in making entire teams and departments more productive by automating low-level, time-consuming tasks and offering a visual overview of manufacturing, designing, and selling processes How AI and automation will help engineering and humanity.

5. Collective Intelligence: Looking towards the future, AI in engineering is expected to focus on collective intelligence, where engineers and AI systems collaborate closely. This collaboration aims to identify problems and develop solutions more efficiently, enhancing the design process and operational systems. This approach underscores the importance of human-AI collaboration in driving innovation and efficiency Engineer Innovation — Stories, Thoughts and Trends for a Better Tomorrow.Issue 8, 2021. (requires registration and download)

Engineers have found various uses for AI in engineering, including robotic automation, materials science, and text-to-design applications. Practicing engineers recognise the value this brings. Streamlined tasks lead to increased efficiency, more powerful problem-solving solutions are available with predictive maintenance too as well as improved design optimisation and safety procedures. (source: Monolith.com)

Project managers will find their role augmented by AI’s capability to analyse data for project insights. Gaining proficiency in data analysis and AI software could give you an edge in overseeing more complex, AI-driven projects. 

For example:

1. Resource allocation AI algorithms can analyse project requirements, team skill sets and availability to optimise resource allocation for projects.

2. Risk management AI systems can continuously monitor project data and identify potential risks, allowing project managers to take proactive measures to mitigate them.

3. Real-time tracking With the help of sensors and AI-powered tools, project managers can track progress in real-time, providing them with accurate and up-to-date information on project status.

4. Predictive analytics AI algorithms can analyse past project data and identify patterns to predict potential delays or issues in current projects, allowing project managers to take corrective actions before they occur.

5. Automated scheduling AI-powered tools can automatically schedule tasks, set deadlines, and assign resources based on project requirements, saving time for project managers.

Scheduling Example

One critical responsibility of a project manager is creating a schedule. Traditionally, most companies have been relying on predefined schedule templates that contain commonly needed phases, milestones and tasks. However, this static approach to controlling the quality of a schedule may soon be a thing of the past, as AI can generate highly complex and accurate schedules by analysing all available data.

In an experiment, we used empty schedules and asked project managers to describe the context of the initiative. In return, a full work breakdown structure (WBS) and schedule were generated within seconds. As we trained ourselves to describe the context better, the schedules became more accurate. Simply stating the context as "ERP implementation project with a 12-week duration" could be improved by adding more context, such as "global roll-out of a new ERP system to five regions following the PMBOK methodology, starting the second week of May 2023 and to be finished a year after.

In roughly 30 seconds, a full schedule was returned, containing all the requirements, the proposed task duration and a score that reflected the likelihood of the AI's estimation of the task duration. This alone could save project managers hundreds of hours, and it could also assist the PMO in creating better templates as they connect their own experience to the rest of the world. The output could surely lead to more accurate schedules, better resource allocation and, ultimately, more successful projects".

Source: https://www.forbes.com/sites/forbestechcouncil/2023/03/30/how-ai-is-revolutionizing-project-management-three-use-cases/?sh=388827a32cb1

Executives also must refine their ability to lead in a tech-driven environment, cultivating an understanding of AI's strategic implications and fostering a culture where innovation thrives.

Here's some specific examples of how AI can assist C-suite executives 

Predictive AnalyticsSophisticated AI algorithms can analyse past and current data to forecast trends, identify opportunities, and anticipate risks. This involves examining market conditions, competitive dynamics, and emerging patterns, thus equipping executives with the foresight to craft resilient strategies.

Scenario Planning With AI's ability to simulate various business scenarios, executives can visualize the impact of different strategic choices. This aids in contingency planning and helps ensure that strategies are adaptable and responsive to potential shifts in the business landscape.

For organisations needing to keep pace with ever-changing market trends and consumer demands a more data-driven approach to decision making can assist in staying competitive. AI-powered analytics software can analyse customer data, sales trends, and product performance in real-time, enabling data-driven decisions on inventory management, pricing strategies, and marketing initiatives, allowing for adjustment to business strategies. By leveraging AI, companies can identify patterns and insights within vast amounts of data that would otherwise go unnoticed. These insights can lead to the development of new products, entering new markets, or even revamping business models.

Alibaba Adobe and Netflix

Netflix's use of AI in content recommendation is a brilliant example of using AI to drive business strategy. By analysing viewing patterns, preferences, and behaviors of its millions of subscribers, Netflix uses AI to not only recommend personalised content but also to make strategic decisions about what kind of original content to produce. This strategy has contributed to Netflix's position as a leader in the streaming service industry.

Alibaba, the Chinese e-commerce giant, uses AI for predictive pricing and inventory management. By analysing historical data, current market trends, and customer behavior, Alibaba's AI algorithm can accurately predict demand for products and adjust prices accordingly. This strategy has not only increased sales but also reduced waste and costs associated with overstocking.

Adobe, a leader in tech and creative software solutions, has also integrated AI into its strategic planning process through its platform, Adobe Sensei. This AI-powered tool analyses consumer behavior and preferences to provide valuable insights for product development and marketing strategies. As a result, Adobe has been able to better understand its target audience, deliver personalised experiences, and increase customer satisfaction.  They also sell the product to consumers. 

Partnerships with AI: Collaboration Not Competition

AI's capabilities are best harnessed when viewed as a collaborative partner rather than a competitor. This paradigm shift involves recognising the potential of AI to extend human capability, not replace it. Each task that AI automates frees up more time for engineers, managers, and executives to engage in higher-order thinking and strategic planning.

Leveraging AI for Enhanced Decision-Making

Armed with the power of AI, professionals can make more informed and precise decisions. AI's ability to process large volumes of data at exceptional speeds enables finer analytical insights. For professionals, this means adopting a data-driven decision-making approach, where intuition is supplemented by concrete analytics.

Staying Ahead of the Curve

Innovation remains key. Stay informed about emerging AI trends and potential applications within your field. Remain proactive, seeking out AI initiatives and expressing willingness to lead pilot projects. Your initiative could become the beacon for change within your organisation.

In Conclusion

The dawn of AI is not the end of the professional road; it's a pivotal turn towards a new trajectory of growth and development. By implementing a strategy that focuses on education, collaboration, and innovation, you can future-proof your career against the inevitable rise of AI. Whether you are an engineer who designs the AI, a project manager who orchestrates its implementation, or an executive who strategises its integration, the future is ripe with opportunity.

Take the reins. Engage with AI from a position of knowledge and confidence and choose how AI will impact your career and not the other way around. 

We would love to hear if AI having an impact on your day-to-day worklife? Have your or your organisation adopted AI into the  business processes and procedures? Or perhaps in other ways?

We’d love to hear your comments as we value your thoughts and engagement.

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References

1. Resource allocation: "Resource Allocation Optimization in Project Management Using Artificial Intelligence" (https://www.researchgate.net/publication/321684503_Resource_Allocation_Optimization_in_Project_Management_Using_Artificial_Intelligence)

2. Risk management: "AI for Risk Management – Identifying and Mitigating Risks Before They Happen" (https://www.cognilytica.com/2018/07/11/ai-for-risk-management-identifying-and-mitigating-risks-before-they-happen/)

3. Real-time tracking: "The Role of AI in Project Management" (https://www.pmi.org/about/blog/new-gen-project-management-role-of-ai)

4. Engineer Innovation — Stories, Thoughts and Trends for a Better Tomorrow.Issue 8, 2021. (requires registration and download)
5. How AI and automation will help engineering and humanity
6.  https://research.netflix.com/research-area/machine-learning 
7. How Alibaba is using AI to power the future of business] https://www.forbes.com/sites/bernardmarr/2023/10/04/the-amazing-ways-chinese-tech-giant-alibaba-uses-generative-artificial-intelligence/?
8. https://business.adobe.com/au/