AI has undeniably proven to be the future for business.
With that in mind, there is a huge difference between understanding that artificial intelligence is the future of business and implementing AI within your company successfully.
The latter, AI adoption, is where most companies are stuck.
Even though nobody said that digital transformation would be a straightforward task, you are not the only one who assumed artificial intelligence adoption would be a piece of cake.
Nevertheless, the present-day AI can work wonders – it can process invoices, change marketing messages in real-time, and translate languages.
The problem comes in implementing the technology.
Even though AI is intended to simplify business life, real-life situations sometimes fail to work.
If your business has not succeeded in implementing your AI projects, there is no cause for alarm since you are not the only one experiencing such challenges.
Here are 6 reasons that may be preventing the full adoption of AI in enterprises around the world.
Operating artificial intelligence without sufficient data is similar to driving a vehicle without gas.
Nevertheless, a recent study revealed that about 18 percent of firms have implemented a plan for maintaining and accessing the types of data needed for artificial intelligence to run effectively.
If you lack clean, accessible, organized, and relevant data, you can fail to operate optimally.
All in all, only when companies start investing in quality data procurement and management will their AI become effective.
Inadequate infrastructure might be an impediment to AI adoption.
Recent research revealed that 15 percent of organizations have the ideal technological infrastructure needed for supporting artificial intelligence.
This means that companies lack fast systems that can process data fast enough and store the large volume of data needed for artificial intelligence to function optimally.
Inadequate infrastructure or lack of advanced infrastructure required for full AI adoption will always hold you back from enjoying all the benefits of artificial intelligence.
5G will come in handy in fields such as computing at the edge even though the entire infrastructure needs for inference and training include considerable investment in storage and computer systems, which many companies don’t have in their data centers.
Lack of Talent
Most companies can launch AI in some form through a Software-as-a-Service provider that integrates artificial intelligence into their sales or marketing software.
The problem comes with attracting or being able to afford the right AI talent that you require in a bid to develop an effective AI plan across your business.
While large companies may not have a problem with this, small and medium-sized enterprises may lack enough IT specialists and funds.
Also, companies positioned out of key geographic markets may find it difficult to achieve full AI adoption due to the challenges of hiring or attracting the most suitable technicians in their cities.
Lack of a Visionary Leader
Not every leader is ready to accept machine-powered decision-making.
Studies indicate that only 26 percent of senior leaders have a certain level of commitment to artificial intelligence endeavors, and 17 percent of the respondents claimed that their companies had already identified AI opportunities available internally.
Although it could be due to a lack of proper understanding or even fear, one thing’s for sure that not every leader is ready to take their chances when it comes to AI.
Looking at digital transformation efforts, it is safe to say that when a given leader withholds his/her support, it becomes difficult to achieve successful adoption.
In business, you must spend money in a bid to make more.
This is not a problem for large companies like Amazon.
AI is important for Amazon’s recommendation engine, which accounts for 35 percent of the entire company’s revenue.
RBC Capital revealed that the company’s Alexa speakers could help generate an extra $10 billion in sales by 2020.
As such, Amazon can afford to invest millions in AI initiatives.
Sadly, not all companies are like Amazon.
Most businesses have considerably smaller margins.
A Learning Curve
Change does not come easy, especially in digital transformation.
The adoption of artificial intelligence is characterized by a disappointing learning curve.
Due to the above problems, many companies have discovered that what they initially thought would be a straightforward way of increasing efficiencies has been similar to carrying out home renovation – each wall they destroy opens up a new issue that they did not know existed.
This is why many companies have ended up being disappointed upon venturing into AI development.
Nevertheless, there is still hope.
A recent report revealed that 78 percent of enterprises felt that they either experienced moderate or considerable value in their artificial intelligence (AI) investment.
There are huge benefits to be reaped by those who are committed to overcoming the challenges encountered in their artificial intelligence experiences.
Hence, the learning curve may prove to be an excellent opportunity for both new and existing companies to up their game.
Recently, Microsoft revealed its plans to open its AI Business School.
This announcement comes at a perfect time when the company is seeking to provide a broad range of free training modules intended to assist companies in understanding the opportunities and use cases that come with AI.
Other companies in the technology industry may soon follow Microsoft’s example and develop certification and online training programs for both companies and individuals looking for AI training.
Also, the number of trade schools and universities offering Advanced Analytics and AI training can also be expected to grow rapidly in the near future.
In the coming decades, artificial intelligence is projected to be the largest commercial opportunity across the globe, for both countries and companies.
The technology could increase the global GDP by 14% by 2020.
Since this is no mean feat, companies must push forward with AI adoption despite of the challenges.
To do that, they must be completely digitized in a bid to pull and use data across all departments.
Furthermore, companies have to ensure that their AI initiatives are scalable.