Triple Constraint model in Artificial Intelligence Adoption
The success of any project depends on the management of the triple constraint, which often refers to cost, time, and scope. According to research, the triple constraint is the most crucial concept in the history of project management. The model consists of three items, namely, cost, time, and scope. Each has equal vitality in the management of the project.
Cost refers to the financial implications of the project, mostly called the budget. The scope refers to the total tasks involved in the completion of the project. Lastly, time refers to the schedule for the project to be completed. In other words, the success of the project is that the implementation of Artificial intelligence into the market depends on the deadlines, features, and the budget (McKinsey Global Institute, 2019).
The essence of the triple constraint model can be explained in terms of the boundaries in which one works. It provides a framework that every stakeholder in the artificial intelligence agrees on. Notably, they drive the project toward success while allowing amendments to be made when sensitive issues arise during the project management. According to studies, managing IT projects follows a series of trade-offs and compromises, which drags along the completion of the projects. Thus, it helps the managers to estimate the requirements, exchanges, and means for successful emerging technology installation.
The financial commitment of artificial intelligence is depended upon many variables. Various resources such as people, material, and labor incur costs to the organization in adopting artificial intelligence. Besides, other outside forces can impact a project, which must be considered in the value of the work. All these must be considered during project planning to ensure the chosen technology is successfully implemented in the organization.
It is also important to note that there are also fixed and variable costs inherent in any project, such as the economic cost of teams with varying skills and productivity, which must be calculated. This can seriously come into play with the use of contract workers or outsourcing. For effective management, the organization should estimate costs to figure out the needed financial commitment for all resources necessary to complete the job. While cost budgeting creates a cost baseline, cost control manages the fluctuation of costs through the project.
As earlier mentioned, scope deals with the total sum of all tasks involved in completing the project. Artificial intelligence involves numerous studies ranging from software development to testing and implementation. Understanding project scope helps the management to work in time and budget and void wastage of resources.
Management of project scope requires one to prioritize tasks and plan to work on tasks that need urgent completion. Prioritizing tasks also enhance the assignment of tasks and resources effectively. Lack of order in project management leads to people becoming overwhelmed, creating room for scope creep. Every prerequisite task must be completed satisfactorily before moving to the next.
Another critical factor to consider in scope is handling stakeholder’s expectations. Often, stakeholder s have dynamic demands which pop up anyhow, and you need to assuage such expectations for smooth project management. This can especially be the case in the long term artificial intelligence projects where there might be new stakeholders introduced in the middle of the project.
Following the likelihood of change in expectations, the organization must be sharp in managing change. Change management is critical in the management of the project scope. These include the management of change requests. In such cases, project managers are devised to accommodate all claims that are critical to the achievement of the goals and deliverables. In summation, all aspects of the project scope are essential in the accomplishment of the project as a whole.
As earlier mentioned, the schedule is the allotted time for each task in the project. Overall, the time takes to complete the project and successfully have artificial intelligence applied in the organization depends on the completion rate of every single task in the project. For successful completion, a work breakdown structure (WBS) is to be adopted so that the project is broken down into manageable, simple tasks.
Besides, a Gantt chart can be used to visualize the schedule of the project with each task-duration linked effectively on the map. Notably, historical data is essential in arriving at accurate estimates. The process of time management in any project involves various steps. They include
- Plan Schedule management which involves the creation of policies, procedures, and documentation for project management\
- Define activities. This involves identifying and documenting the actions required in producing project deliverables.
- Sequence activities. It identifies and documents the logical order or work to be most efficient
- Estimate activity resources and duration. Takes into consideration the time and amount of resources needed to complete the project.
- Develop a schedule. It analyzes activity duration, resources ad timeline.
- Control schedule. Comparing planned schedule to actual progress to determine if your project is on track
Forces that Shape Artificial Intelligence Future
Emerging technologies and techniques are freeing IT leaders to reduce costs, save time, and let machine intelligence do almost everything. The field of IT is on the precipice of unprecedented change. Nearly all companies are experiencing glimmers of massive shifts, including automation, decentralized technology budgets, rapid adoption of cloud-based services, and artificial intelligence.
Notably, the emerging trends in technology have led to a massive change in the routine of works, from warehouses to the C-suite. Enormous data is ingested in real-time, while business decisions are offloaded to machines. This has created more time for human agents to focus on planning, pursuing leads, and adopting new technologies. Below are nine factors that are shaping the future of IT, especially Artificial intelligence. The elements are listed according to their predictability and importance, as will be shown in the following graph.
It is conspicuous that automation is rapidly becoming mainstream. It is moving from experimental projects to the real business world. Automation is projected to create an impact on the IT world, which will be freedom for the IT field to be more strategic. However, many suggest that half of the jobs performed by people today may be performed by machines using existing technology.
According to research, “Finding, extracting, and conforming all this information so it can be used to drive decision-making has been a complex and labor-intensive task for decades” (Heltzel, 2017). Another one says, “I see the biggest impact that automation will make on IT is that it will accelerate the shift from ‘running IT’ to innovating for the future” (Adams, 2019). All these are but an expression of the expected impact of automation on the end of artificial intelligence. As more tasks are automated, AI becomes readily accepted and adopted in society.
Automation is leading to increased speed and agility at workplaces. What used to take decades now takes a couple of hours to be in place. In the banking industry, people used to make withdrawal requests months to the due date. Today, you can withdraw your money anytime, anywhere. Such is the speed change that has taken place in the IT world. With the same projection, artificial intelligence will be critical in any social, financial, and technological developments in society (Westland, 2018).
Costs ad budgets
The increasing use of IT in every sector will make companies change their view of budgets and how technology is developed and maintained in the organization. In short, the percentage of technology cost is increasing in the funds of companies across the world.
Of course, along with opportunities, rapidly changing technology also introduces new problems –both in identifying holes in security and finding the talent to address them. As this threatscape evolves, IT may see protection cease to be an isolated function and instead become an integral element of everyone’s job.
There is going to be a deeper collaboration between IT and other business units, including human beings. The shift in spending doesn’t have to mean a complete change of power.
Other factors that will shape the future of artificial intelligence include agility, flexibility, ubiquity, and symbiosis.