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Challenges In AI Adoption and How to Overcome Those

Applications powered by artificial intelligence (AI) are reshaping the way businesses operate and, by extension, how people live their lives. The most recent use case of AI adoption doing rounds over the digital space, for instance, is ChatGPT – which could herald the next stage for workflow optimization and customer experience for different companies.

McKinsey’s research shows that the spread of AI has increased steadily since 2021. 56% of respondents report using AI for some aspect of their business, up from 50% in 2020. But as we know, every technology is a pandora’s box full of possibilities and challenges.

Which AI developments should companies watch out for in 2023 and how they will prepare themselves for AI adoption is a question to ponder. To that end, let us examine what is in the store for the future.

Top 5 Challenges to AI Adoption

Even though most firms see AI adoption as integral to business success, doing so can be challenging. To what extent do the adoption obstacles prohibit businesses from tapping into the enormous potential of the technology? Let’s discuss.

Lack of Requisite Skills/ Knowledge

Inadequate skills and the lack of requisite knowledge is the first barrier. In the eyes of HR managers and CIOs, AI will reshape the skills necessary to drive ambitious initiatives. For instance, AI can currently do X-ray evaluations on par with human radiologists. In the future, radiologists will use augmented analytics tools to discuss procedures and outcomes with patients, collaborate with other doctors to diagnose and cure illnesses, and even execute image-guided medical treatments.

However, to realize something of this sort across industries, firms will have to invest in training their employees and recruiting those with the right knowledge, skills, and expertise relevant to AI — we’re talking about niche expertise in ML modeling, data science, etc.

Inability To Identify Appropriate Use Cases

The data collection procedure itself might be a source of bias. If the data comes from a poll in a magazine, it’s important to remember that the respondents represent a niche demographic: magazine readers. We cannot conclude that the dataset generally represents the population in this case.

Knowledge gained in one field may be effectively applied to another with the assistance of our human discernment. The term “transfer of learning” refers to the human capacity to apply knowledge gained in one context to a new but analogous one. However, the ability of artificial intelligence to generalize from one environment to another is still in its infancy.

Fear of The Unknown – How to Adapt, Is It Possible to Adopt?

Employees need a thorough understanding of AI and its potential benefits. Leaders across the business domains and IT, in particular, face challenges when calculating the ROI of AI initiatives. Though the monetary worth of AI-powered democratization initiatives, like analytics, is easy to pin down, others, like customer satisfaction, technical support, etc., are more nebulous and difficult to quantify. This ushers in a host of questions about the viability of AI for a certain business case — only adding friction and confusion against the technology’s adoption.

Data-Related Challenges – Quality of Data, Bias, Data Security

High-quality data is integral to the success of AI-powered initiatives. To obtain this data, businesses have to invest time and money in collecting and refining it. Plus, there’s a need to manage information that’s at times voluminous, stale, or inaccurate. A lack of consistent data quality could compromise the integrity and possible outcomes of AI projects.

So, the data infrastructure, data storage, labeling, and data input — all need to be considered. Also, there’s model training, gauging the value of the resulting AI, creating a feedback loop to constantly improve models depending on people’s behaviors, and data sampling to restrict the amount of data retained while still producing accurate results. There’s, indeed, a lot to consider.

Cultural Change

Two of the biggest obstacles to widespread AI adoption are organizational resistance to the technology and the issue of developing viable business use cases – as has been discussed above. Managers need an in-depth understanding of AI technology and its potential applications to build a strategy for its use.

A lack of AI knowledge might do more harm than good. Challenges don’t end here, though. Some companies rush to invest in AI without a strategic plan or without first assessing the value of its application to a particular business case. Implementing AI requires a strategic plan that considers desired outcomes, key performance indicators, resource utilization, and measures of return on investment.

How to Overcome Challenges to AI Adoption?

  • Consult a business analyst to determine which of your company processes and IT systems may benefit from implementing AI.
  • Take into account how moral or ethical concerns might limit your use of AI.
  • Build a prototype (or an MVP) to determine whether the proposed solution works; identify potential roadblocks to realizing success with AI.
  • Create a comprehensive plan for rolling out your AI project, keeping the relevant stakeholders in the mix.
  • Keep your expectations high; however, be patient about AI-powered process improvement, for it can evolve.
  • Bring in experts to help fine-tune AI systems.
  • Inform the workforce about the value of data-driven decision-making and the potential for optimization using AI.
  • Train them on leveraging the AI solutions in place to the desired extent.
  • Replicate the success and mitigate the failures of your pilot project based on process improvements seen, anomalies identified, and ROI assessed.

Wrapping Up

PwC estimates that by 2030, artificial intelligence will have added $15.7 trillion to the global economy. About $6.6 trillion is anticipated to result from enhanced productivity, while the remaining $9.1 trillion is expected to materialize from consumption-side impacts. Though there may exist challenges/drawbacks to any new technology’s adoption, it’s essential to focus on the advantages and figure out strategies to overcome the challenges.

Looking to achieve revolutionary growth and optimize profits by overcoming the hurdles to AI adoption? We can help. Get in touch to learn more about we can assist you in developing and implementing winning AI solutions.

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