Your Digital Strategy: How to Plan AI Implementation
By now, you likely have a pretty good idea of what digital advancements can do for your business. But, as we already mentioned, AI, ML, and DS must be introduced in a purposeful, meaningful way to truly generate the kind of benefits you were hoping for.
Set Your Goal: Why Are You Doing It?
Your AI implementation strategy needs to be active and clearly defined, with a clear plan for how it will be navigated and controlled. In a sense, you should opt for a holistic use of AI. This means that any updates you make in this area must target the most relevant areas, and the implementation must be done across the board. You should make sure that not a single aspect of your business gets neglected when evaluating the potential impact of new technologies. You also need to think about how the improvements will affect your employees, from work tasks to new employee skills that will be needed to utilize the new technologies.
For this, it’s important to define what degree your processes should be altered. While research does show that companies that undergo digitalization benefit at least a 25% bump in productivity (Cappa et. al., 2021), this benefit will only occur if you match the technologies well with your processes.
AI Introduction: Are Your Employees on Board?
Almost every new job ad nowadays requires a potential candidate to think outside the box and be open to learning new skills and working with new technologies. This isn’t without a reason. Not everyone appreciates new technologies, and no matter how well-trained and experienced your employees are, if they aren’t well-adapted to change, the new technologies that you install won’t be used to their full capacity. The best way to find out what your staff’s tech mindset is is to nurture a culture of transparent communication about all the topics that are relevant to them, technologies included.
Many successful businesses let employees participate in choosing machines and software that will be used if they will be the ones using them. You might know your company inside and out, but the people who are doing specific tasks can better perceive which designs are best suited to assist in their roles. If you keep your employees well-informed of your plans to introduce tech improvements, the chances of them accepting digitalization with enthusiasm are higher.
To Buy or to Build?
While you can purchase and download licensed installations for dozens of AI software, statistics show that, although more expensive, building systems that are unique to your business is more effective. Building your digital solutions from scratch will be expensive, and it will take time; but, once you begin using the systems, the benefits will accumulate in the form of a synergistic effect. With new tools being added to ease the workload, the office climate will improve, and your employees will have more time to contribute where their talents are most needed. Additionally, your customers will appreciate a more personalized experience, which will result in more profits.
Furthermore, streamlining workflow will result in major cost cuts, and all these benefits combined will soon transform your business. With data analysis software and experts to track the completion of your business goals and make relevant predictions, the path toward your goal will soon become much clearer.
Risk Management
Risk management is an essential part of any strategic plan, and it’s present in designing your digital transformation. Here, you need to think about several potential AI risks, and what will you do to prevent them, or mitigate the damage if it occurs:
Ethics and Confidentiality
How will you ensure that information gathered by your AI, ML, and DA systems is protected against misuse? How will you show that you’re not accessing your employees’ data with hidden motives or interests in mind? More importantly, how will cutting-edge technologies relate to your company values?
After answering these questions, think about how your company values can be implemented into tech architecture and design.
The Legalities
Just because you have the possibility to access certain information doesn’t mean that you’re allowed to use it. In fact, numerous regulations concern the use of AI in business, from compliance with task laws and civil rights to confidentiality and personal rights to information safety. Moreover, you’ll need to plan for how to comply with regulations that concern business information and consumer information. Although you, as a company, don’t intend on misusing this information, certain data that normally wouldn’t belong with your company could end up on an office device. So, ensure that you have clear guidelines in place for information flow across your systems, as well as confidentiality rules and communication decorum, that will record all necessary data on company laptops.
Onboarding
How do the new technologies reflect on your current workforce? Will they make certain skill sets unnecessary and leave room for new ones? Technology can replace human labor to a degree but getting rid of employees isn’t the best idea. Not only will this result in most work tasks not becoming automated, but it could also affect your employees’ potential to bring in more profits and build new skills. Introducing AI into your business will require you to redistribute the workforce, reevaluate the required skills, and provide adequate training for them to use the new technologies properly.
The more your company relies on technology, the more expertise will be needed for your systems to run smoothly. This means that you will need a certain number of IT and DA experts and hire the right talent.
Training and Troubleshooting
Your staff won’t only need the training to use the latest technologies, but also the knowledge of how to do it in an ethical way that won’t expose your company to liability or accidentally share confidential information. Your employees need simple-worded instructions for how their workday will look with new technologies, and how to intervene when your AI systems and their procedures get in the way of a smooth workflow. This means having protocols for circumventing any challenges that might occur if your systems crash or begin to underperform.
Civil Rights and Bias
Although AI promises to introduce more equality and fairness into offices, monitoring is still needed to ensure that there’s no accidental bias or discrimination. One of the notable examples would be how AI software that detects people’s preferences may begin to discriminate or stereotype people. Let’s say that your algorithm displays ads and offers based on geolocation, personal preferences, race, or ethnicity. Despite that you may not intend this, it could become biased against consumer minority groups if cultural factors are too emphasized. Your new products might get advertised only to a portion of your audience, or your minority users might get poorer customer service if the algorithm begins to prioritize customers from other larger segments.
All of this happens because the software can’t really figure out that just because a user comes from a group that’s somewhat less represented in percentages doesn’t mean that they shouldn’t be given equal attention. Some real-life examples include suggesting poorer-quality products and services to minorities based on geolocation and even confusing customer identities. Sadly, research shows that the same pattern-oriented nature that makes AI so magnificent in operating independently can exclude people who don’t fit the preset patterns.
IT Diversity
If you thought that machines are immune to racial bias, think again. Studies show that people who create these technologies unintentionally imprint their own cultural influences. Facial recognition performs best when scanning white males, demonstrating a clear bias against people of colour. Thus, you need a diverse team of experts who will infuse a multitude of cultural patterns into their work, broadening the reach of your new systems.
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