By now, most people recognize that artificial intelligence (AI) isn’t the world-ending technology predicted in science fiction — yet. But AI is one of the tech developments shaping the present and changing the world quickly.
Experts predict that within just a few years, almost every industry will be transformed by artificial intelligence. Already, industries as disparate as food services and construction are utilizing AI solutions to improve operations and fuel growth; real estate, education, healthcare, cybersecurity, hospitality — name an industry, and it is possible to find organizations experimenting with AI-driven tools.
As AI and robotics adoption increases, funding for AI development also increases. AI technologies are becoming more complex and better at delivering business solutions. Currently, only the most rudimentary type of AI is in use: “narrow AI.” This form of artificial intelligence can only perform a specific, narrowly defined task, such as performing facial recognition or producing an image. Yet, because AI has become so popular, some experts anticipate a leap to “general AI,” a more sophisticated type of AI, by the end of the decade, and superintelligent AI likely won’t be far behind.
As AI development accelerates, it drives another high-tech industry: robotics. Advanced robotic solutions are becoming widespread as more businesses recognize the advantages of having specialized robots.
Many economists believe we are in the midst of another industrial revolution, one in which businesses that fail to adopt AI tech risk becoming totally obsolete. Fortunately, it isn’t too late for you to make strategic changes allowing AI and robotics integration. If you feel late to this paradigm shift, you can use this guide to strategic AI and robotics adoption to make the necessary changes to keep your organizations alive and thriving in the AI-driven future.
Creating a Vision
If you want to adopt AI, you must first understand all available solutions. The best way to start the journey to AI implementation is by exploring a business’s current processes and looking for areas where AI can improve — like inefficiencies, repetitive tasks, or other pain points. You’ll also need to ensure your data is good to go, as well as have a good understanding of what tools you may already have, so you’re prepared to use new tools to their fullest extent.
Once you identify specific problems to target with AI or robotics, you can begin developing objectives for initiatives that will guide AI and robotics adoption. This is perhaps the most important step in adopting advanced tech like AI and robotics. At this stage, you will identify opportunities and obstacles that are essential in creating a strategic map. During this step, you should consider the metrics you will use throughout the adoption process to measure the effectiveness of implementations. The vision phase also involves acquiring buy-in from stakeholders affected by the shift toward AI. The key is to align AI goals with broader business strategy to ensure long-term business success.
Assembling a Team
AI integration and maintenance are technically demanding and require the attention of a cross-functional team of AI experts from both internal departments and external firms. You will need to coordinate IT, data science, and operations with dedicated AI specialists to build and deploy AI solutions to meet needs and achieve goals. Businesses interested in the implementation of robotics alongside AI will need robotics engineers within the team, as well. As the team comes together, every member must know their role and responsibility in developing and implementing AI to ensure efficient progress and success.
Preparing Underlying Systems
Rarely does advanced technology consist of plug-and-play tools. More often, cutting-edge tech is utterly revolutionary, requiring integration with several types of hardware, software, and data systems that are drastically affected. Before businesses can successfully implement any radical technology, like AI or robotics, you must review and make necessary changes to any processes and systems that the new AI solutions will rely on. It will likely be essential to upgrade or enhance certain systems to ensure proper support for cutting-edge AI tools.
Most AI implementations rely heavily on data, which means you will need to pay particularly close attention to their existing data structures. It might be necessary to create new databases that are more accessible to AI tools. Additionally, you should update their policies on data usage to protect any sensitive information that may be fed into AI systems.
Training the Workforce
Though many AI developers strive to make their solutions intuitive, it is not unusual that employees struggle to adapt to changing processes and new technologies. It is one thing for you to understand the benefits of AI and robotics in improving efficiency, safety, and other aspects of workflow; it is another for the workforce to accept these tools and use them effectively. Businesses should implement change management strategies to help staff adjust through the AI implementation process. In some circumstances, offering training and development programs may be useful so workers can become proficient with whatever advanced tech they will use going forward.
It may also be a good time for you to assess whether you need to add any AI specialists to your staff. Not all organizations need in-house AI workers; outsourcing this expensive skillset is often advantageous to smaller businesses with more limited AI implementations and smaller budgets. However, organizations with radical AI strategies will likely benefit from specialists who can provide oversight and maintenance to robust AI systems as needed.
Experimenting With AI
Before engaging with a full-scale implementation, you should thoroughly vet your chosen AI tools. AI solutions have risks and advantages, and it is smart to know exactly how specific AI applications will impact your company before you apply them on a broader scale. Pilot projects allow staff to monitor AI and robotics solutions to better understand feasibility and effectiveness. Small-scale testing is more affordable, less disruptive, and has the potential to provide more meaningful feedback because it takes place in more tightly controlled environments. This is especially true for robotics. You may expand or diversify AI experimentation as testing generates positive results.
Preserving Integrity
Any new digital technology can negatively impact cybersecurity, and because AI requires such extensive amounts of business data, it is imperative that organizations do the utmost to update protections before and throughout the AI adoption process. A data breach of any magnitude is exceedingly costly, both financially and reputationally, so any new AI tools mustn’t expose businesses to undue cybersecurity risks.
Ethical and legal guidelines surrounding AI and robotics use continue to shift as the technology evolves and expands. You must adjust AI strategies to remain compliant with developing AI laws and regulations. It might be beneficial for you to engage stakeholders in discussions regarding the ethical application of AI and robotics; such conversations can lead to the development of in-house ethical guidelines that address workforce concerns and align adoption practices with the needs and expectations of the organization.
Implementing AI
Eventually, businesses reach the implementation stage, but this stage is far from the end of the AI adoption journey. Rather, organizations should roll out AI or robotics slowly in manageable phases. Starting with small, easy-to-manage projects can help demonstrate the value of AI and robotics to stakeholders and increase support for large-scale programs and initiatives.
It can also help reveal challenges for human-robot collaboration you didn’t identify in the earlier research and testing stages, such as hurdles related to safety and morale. Keep in mind that working to overcome these challenges, however, allows you to reap benefits, like boosted productivity and error-free work.
You should employ all the same methodologies for review and assessment as used in the experimentation phase to continuously evaluate the performance of the new tech and make adjustments as necessary to ensure success.
Expanding AI
Slowly, you can begin to increase AI’s influence across the organization. First, you might opt to scale up successful AI projects or robotics applications, extending their reach to deliver more extensive, more impactful benefits. It might be worthwhile to consider how small-scale projects may be adapted to deliver advantages across business departments to improve overall efficiency.
As staff gain greater comfort and confidence using AI solutions, consider adopting new AI solutions in new departments. HR, finance, marketing, operations, and other departments stand to benefit from specialized AI solutions. For example, AI tools may help you in these areas make better decisions or improve productivity amongst staff by automating certain tasks. Such broad AI use can help make an organization more competitive in current and future markets.
Assessing Success
Business change is only complete once you have conducted a robust assessment of its effects. Though assessments should occur between every phase, once AI and robotics have been implemented on a broader scale, you must conduct systematic reviews of the new systems to determine whether their chosen metrics indicate that chosen goals for AI adoption have been achieved.
AI and robotics tools are expensive, but you should consider them investments in an organization’s future. Still, you may want to conduct regular ROI assessments to better understand how much these new technologies are costing, how much value they are providing, and how a business may continue investing in AI or robotics in the coming months or years.
Like it or not, AI is inextricably linked with the foreseeable future of business. The sooner you make meaningful moves to integrate cutting-edge AI and robotics technologies, the sooner organizations can avoid a slow and devastating slide into obsolescence.
