In Belgium alone, three out of four companies now report making use of AI to support one or more of their business processes. Although many of them like to put these initiatives on display, we often see the same challenge reoccurring: the power of AI is ready to be unleashed, yet it suffers from severe organizational delay. Therefore, those who can transit into a full AI integration the fastest will gain the most competitive advantage.
From our day-to-day experiences, we boiled down a list of common decelerators to four major barriers. Understanding how to elaborate on these will allow you to accelerate the organizational shift necessary to become truly AI-powered!
In a nutshell, the main stumbling blocks are:
- Lack of data accessibility.
- Lack of cross-departmental collaboration.
- Lack of general trust in AI.
- Lack of top-level engagement.
Let us break them down for you.
Technological progress has made the storage of data easier than ever before. Leveraging the available data however has proven to be much more challenging. Data sources are often very much dispersed throughout an organization. As AI implementations almost always require a combination of these sources, the challenge resides in linking all existing information into one centralized ecosystem.
Yet, even when data have been brought together, it is not always easy to find the person that can grant access to the source of this information. These gatekeepers are needed in the context of data security, but can unnecessarily prolong data projects. For example, the periodical extraction of csv and excel files always adds a manual layer to processes that are ought to be fully automatized.
Our advice: shift your organization to a higher gear in AI by gathering the right profiles and giving them the right accesses to different data sources.
Diversify and conquer
AI projects are frequently performed in almost complete quarantine by an isolated team of technical experts. The power of AI however, reveals itself when supported by a mix of technical, operational and analytical profiles. Not only does a diverse set of perspectives offer new insights that boost the performance of AI, shared responsibility also raises the chance of the model being embraced by end-users.
Besides the right mix of profiles, the involvement of multiple departments is crucial for a successful AI implementation. It ensures that projects are set up which are generalizable company-wide, rather than department-specific. In addition, a cross-department collaboration unveils the opportunity of knowledge sharing. This significantly accelerates the growth of internal expertise!
Over the last few years, AI has been in the light of many doom scenarios. As a result, there are employees, especially those who are far from anything that has to do with algorithms, who fear the arrival of AI. Although critical consideration must be given to the labor market of tomorrow, todays AI implementations are not as impactful as many believe them to be.
In fact, most of the present-day use cases in AI are about helping employees automate repetitive tasks so they can focus on the core of their job. If you want to invest in AI, you need to show your employees how it can facilitate their day-to-day work.
A content marketer for instance, may have the idea that AI has nothing to do with his/her job. Yet, you could change this perception drastically by showing the possibility of AI to automate content labeling so that he/she can focus more on writing inspirational text.
Growers and showers
A last consideration on how to shift culture towards full AI integration actually includes all aforementioned issues.
It all comes down to a core question that C-level management in your organization needs to answer: are we doing this 'AI thing' to show off and gain a few extra customers in the short term, or do we take an approach that uses AI as a source of sustainable growth in the long-term?
In case of the first scenario, it is highly doubtful that AI will ever create a meaningful impact on your business. In case of the latter however, leaders can start identifying the obstacles present in their own organization and use these to accelerate the shift towards serious AI implementation!
As of lately, The Reference has been helping organizations make the shift towards an AI-driven environment. Our team of business-technical experts can distill your business needs and translate them into the right AI implementation. These so-called analytic translators can be found across our teams and purposefully assigned to any digital project.
Want to know more about how data and AI are radically changing the current business landscape?