Tutor discussion
Hypothetical Case Simulation
You are the CEO of business (in an industry you will select) that is considering a new AI application called Dublin-10, to automate a system and bring efficiency to operations. An ROI study has convinced you this innovation will enable the business to eventually save costs and almost immediately expand production. However, it also will result in elimination of some employees’ job duties and at the same time increase other needed work.
To avoid having to lay off employees whose work will change as a result of this innovation, you plan to roll out a retraining program for affected employees, as well as conduct the training required for the Dublin-10. None of this has been announced to employees.
As the business’ CEO, prepare and post your response to the following.
DISCUSSION PROMPT:
The hypothethical is purposely generic. For your initial response in this Discussion, there are two parts: posting a narrative and a video.
1. Choose a specific industry and create a hypothetical business for this case. In a sentence or two, for context, describe the company and its industry.
2. You have done the ROI, determined need, and impact on workforce job duties.
What else should you consider? There are several management concerns when implementing change, but for this Discussion post at least
one (1) other planning concern or action you should cover specifically relating to your hypothetical business’ implementation of the new AI, Dublin-10.
3. Role play: Prepare and post a 1-to-2 minute
video message to your
company employees announcing the implementation of DUBLIN-10 and the company’s
training and other plans to avoid layoffs. Consider how this should be presented to your work force.
This video can be prepared in this forum using the VIDEO INSERT tool in the Discussion box. Step-by-step instructions are attached here.
In the alternative, you may prepare and attach an MP3 video from your phone or computer and submit to the Discussion using the “INSERT STUFF/MyComputer” tool in the Discussion box tools. Use Firefox or Chrome browser. (Be sure to allow pop-ups.)
OR – You may prepare the video using an AI application with an avatar or AI- assisted narration. If you choose this approach, be sure you do NOT SACRIFICE YOUR PERSONAL TOUCH. For example, begin with your photo and introduction to personalize yourself as CEO to your employees, and then move into your presentation.
NOTE: If you have a technical issue with posting a video, please contact your instructor in advance or email
[email protected] [email]
for assistance.
AI (Artificial Intelligence) and ML (Machine Learning) can offer organisations breakthroughs in their production systems and even a competitive advantage if used thoughtfully and in the right context. The
digital transformation
and its multiple advances have generated pressure on companies, derived from the fear of being left behind, which in turn has resulted in a pre-willingness among leaders to implement these technologies in their companies.
But in most cases, even if adopted, the fundamental barriers remain and few companies have the basic components that allow AI to generate value at scale. Being clear about where the Artificial Intelligence opportunities are and having central and defined strategies to obtain the data that AI requires should be the starting point for any entity that decides to immerse itself in this transformation.
Therefore, before adopting an AI and ML strategy, companies should ask themselves the following questions:
1. What is the problem you plan to solve with AI?
The main thing in this case is to start by defining the problem. What is the company looking for? Is it a machine learning model that can solve it? Is it known specifically what AI systems will be used for?
It is important, on one hand, to detect which types of activities are being inefficient or human capital intensive, and on the other hand, to determine how AI and ML systems can mitigate these problems.
2. What is the company’s plan to turn AI into an opportunity?
How does the company plan to address the problem and implement the solution?
At this point it is essential to know how to reformulate the problem definition in an automatic learning problem and how to implement it in a way that avoids any kind of slowdown or loss of value during the transformation process.
3. Does the company need a temporary or permanent solution?
AI technologies must become part of the company’s core business and must be accompanied by a change of mentality on the part of the management team. The vast majority of success stories are supported by a digital transformation of the company at all levels.
Depending on whether an AI model is needed for a specific action or for the company’s daily processes, it will be decided to acquire a customised product, a standardised solution or a temporary service.
4. Does the company have the necessary data to feed the AI model?
The quality of the AI model is directly dependent on the quality and quantity of data available to the company. The use of AI implies training an accurate and meaningful data model that can feed the AI systems so that they learn to function on their own, therefore, having a quality historical data is key.
Does my company have enough data? Are the data sources that the AI will use are reliable? Does the company have a robust data architecture? In order to answer these questions, it is necessary to have a solid framework of objectives and KPIs (key performance indicators) and a robust data strategy to ensure that it is squeezed in the most valuable way possible.
5. Is this data digitised?
Do I have the data stored in digital systems? To be able to manage the data correctly, they must be digitised, centralised, organised and integrated in different digital tools (such as CRM’s, or ERP’s, SCADAS, etc.) or in databases, CSV files, Excels, etc. If this is not the case, the digitalisation and use of AI of these data can take a long time and sometimes an insurmountable investment.
6. Does the company have the necessary resources for the implementation?
The company must be realistic about whether it really has the necessary resources at the level of human and financial capital to absorb change. Where will we find the expert talent to deploy AI? What is the company’s budget for acquiring an ML model?
In order to achieve a smooth transition and a correct integration of the models in the internal systems, it is key to have a technical team that knows the company and also knows the developer or data scientist. In addition, these teams must be qualified to integrate the models to be implemented into the company’s systems.
On the other hand, the accuracy of the AI model will depend on the budget, equipment and time available to the company to develop it. All this will also determine whether the company chooses an on-demand service or the acquisition of its own model implemented by its team.
7. What are the consequences if AI fails?
AI models work through very sophisticated algorithms and statistical correlations, but there is always a margin of error. Does the company want to implement AI in a process with high variability and a low accuracy rate, or the opposite? What risks and how much investment would be lost if it didn’t work out?
Depending on which systems and data are available, the company must evaluate whether the accuracy of these models is expected to be high enough to proceed.
8. How will AI be integrated with the company’s overall strategy?
How will the company integrate IA with processes and people? Are there turning points where IA will collide with processes?
AI should not be implemented as a stand-alone technology, but as an integrated solution that enters into synergy with all areas of the company to maximise productivity and results. The company must ask itself if the AI model will be able to work together with the rest of the parties and identify what problems may arise.
9. How will this change affect the company’s workers?
To what extent will IA’s ability to automate the activities now performed by workers affect the size of the workforce? Workers can be very sceptical of change and the company must find ethical solutions so that they do not lose their value and motivation.
Effective change programs will focus on specific training and interventions to involve employees and managers in the company.
10. What are the expected returns from applying this technology?
How long will it take for the company to recover the investment? How much will the company’s costs be reduced once AI is implemented? Integrating AI and ML models in a company implies a cost and therefore an important investment.
For this reason, a realistic estimation must be made to determine the parameters of the return on investment. To carry out this plan, the possible performance indicators (KPI’s) should be established, so that the return can be measured and how much value the model is bringing to the company should be calculated.
Are you thinking of implementing AI in your company?
AI opens doors to countless possibilities for businesses, but if it is deployed simply as an experiment, if a specific problem is not identified and a plan of action is not created, then it will turn out to be a worthless proposition and management will see no return on investment.
From
Nexus Integra
we pave the way for the implementation of AI and ML technologies to be an assured success story. Nexus Integra, the integrated operations platform, offers a structured Big Data tool that provides data scientists with the quantity and quality of data needed for AI and Machine Learning applications, as well as the exploitation of the data in any of its applications; native or external.
The native application of Machine Learning allows for the management of different advanced algorithms and their easy introduction into the production process in real time. Nexus Integra as an integral operation center and Big Data platform allows to get the maximum value from the data.
Key takeaways
·
AI can boost productivity if implemented correctly. Businesses that identify specific ways their team can use AI—and then bring in the help of skilled AI consultants—can see greater long-term productivity gains and success.
·
Everyone can use AI. Technical and non-technical teams alike leverage AI at work with the use of chatbots, AI agents, and no-code tools that make it easy to blend generative AI with essential business tools.
·
Hands-on practice helps. Professional instructional designers shared on Reddit that they’ve had success training team members by creating scenarios and tasks that require everyone to use real company data to create podcasts, solve Excel formulas, and more with AI.
·
AI governance matters. Many free AI tools use user data to further train the model; a paid plan may be required in order to keep data out of the training algorithm.
AI Pros & Cons
Summary of Pros & Cons of AI in Business
This table summarizes the pros and cons of AI in business. These have been covered in previous lessons. For further discussion explaining these pros and cons, please read
AI in Business: The Pros & Cons (The HR Booth, 2023) [webpage](this link opens in a new window/tab)
, from which this table is created, in part.
|
Table Caption: Pros and Cons of AI in Business |
|
|
PROS |
CONS |
|
Increased efficiency and productivity |
Job displacement/workforce challenges |
|
Enhanced decision-making |
Ethical concerns and legal risks (e.g., bias, privacy corruption) |
|
Improved customer experience |
Inaccuracy and hallucination |
|
Mitigation of human error |
Lack of human touch and emotional intelligence |
|
Business intelligence and meeting competition |
Initial cost, maintenance, security, and other technical challenges |