The AI-Powered Organization

How the implementation of AI is breaking organizational barriers and changing professional culture before our very eyes

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Source: AI News

Across all industries, artificial intelligence is becoming a key driver of business decisions. The development of these technologies has advanced rapidly, as AI has become more accessible and more affordable to businesses of all sizes. It is estimated that the implementation of AI on larger scales will add $13 trillion to the global economy[1]. While artificial intelligence has had a widespread impact, many efforts to implement these technologies have come up short.

The Harvard Business Review interviewed thousands of executives to see how their business was taking steps to implement AI and they found “that only 8% of firms engage in core practices that support widespread adoption. Most firms have run only ad hoc pilots or are applying AI in just a single business process”.[2] It seems that many of the challenges of AI adoption are not technical or developmental problems, but rather organizational and cultural barriers that must be broken down through careful planning, implementation, and training around the purpose and use of machine learning technology.

Current Challenges to Implementation

One of the biggest problems faced by businesses adopting artificial intelligence technology is the misperception that AI is a “plug-and-play technology” that will simply generate results.[3] Major investments are made into AI software tools, data infrastructure, and development in order to generate these quick wins; however, many companies fail to reach longer-term success because they think too narrowly about the benefits and larger, future uses of machine powered technologies.[4] “While cutting-edge technology and talent are certainly needed, it’s equally important to align a company’s culture, structure, and ways of working to support broad AI adoption. But at most businesses that aren’t born digital, traditional mindsets and ways of working run counter to those needed for AI.”[5] To maximize the potential of artificial intelligence adoption, many businesses must work towards changing these traditional views to fully embrace the digital era.

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Source:  TechTraining

Preparing for Successful Adoption

Artificial intelligence development requires interdisciplinary collaboration between teams of both business and operational workers, up-and-down the company hierarchy to account for the diversity in human thought, judgment, and intuition. Not only will this allow for algorithms to become more finely tuned and precise, but it will also increase the chances of company-wide trust towards AI and ultimately, empower informed decision making.

In the early stages of development, it is essential to employ a test-and-learn mentality to view mistakes and potential sources for improvement and discovery, all while reducing the fear of failure or lack of initial success. “Such fundamental shifts don’t come easily. They require leaders to prepare, motivate, and equip the workforce to make a change.”[6] Leadership and proper executive planning are equally, if not more important, than early tech development, which will inevitably improve over time. Executives must first prepare for the organizational and cultural changes which artificial intelligence is bringing into all industries today.

Leaders must build and retain both excitement and trust in artificial intelligence technologies, in order to quell fears of standard worker’s tasks becoming obsolete. It is essential to keep in mind that humans working in conjunction with AI-driven insights and analytics will always be more accurate and powerful than either humans or AI working by themselves. The barriers to change must be identified, understood, and properly mitigated by making the benefits and uses of AI clear and by offering incentives for workers to embrace such technologies.

Budgeting for Training, Implementation, and Integration

Further research by the Harvard BusinessReview suggests that budgeting for the integration and adoption of AI plays a more important role than budgeting for development alone. “90%

of the companies that had engaged in successful scaling practices had spent more than half of their analytics budgets on activities that drove adoption, such as workflow redesign, communication, and training. Only 23% of the remaining companies had committed similar resources.”[7] This reinforces the notion that many of the key challenges surrounding the implementation of artificial intelligence are, in fact, rooted in organizational structure and business culture.

To optimize the adoption of AI into ongoing processes, there must be top-down education, to ensure that teams share a singular vision and attitude towards new technologies. Furthermore, it is important that teams remain motivated in the process of AI development and implementation since most adoption processes take between 18–36 months to complete.[8] Leaders must first demonstrate their ongoing commitment to AI, setting an example for the rest of the hierarchy. Additionally, team members must be held accountable, as responsibility for both successes and failures must be upheld.

Over time, tracking and comparing the results of algorithms remains essential in order to make necessary and effective adjustments. Finally, executives ought to provide incentives for change and progress with AI, rewarding those dedicated to the furthering of its implementation. Without actions aimed at addressing the organizational and cultural challenges of AI adoption, efforts may burn out and progress may be limited or slowed substantially.[9]

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Source:  TechCrunch

Conclusion

“The actions that promote scale in AI create a virtuous circle. In time, workers across the organization absorb new collaborative practices. As they work more closely with colleagues in other functions and geographies, employees begin to think bigger — they move from trying to solve discrete problems to completely reimagining business and operating models.”[10] From here, the cycle speeds up as more employees have the test-and-learn mindset which first drove AI adoption.

Once implemented successfully and launched to scale, the traditional organizational hierarchies become flattened, as all play critical roles empowered by artificial intelligence. New possibilities for collaboration and creative thinking are created when an entire

organization is able to embrace and work together through artificial intelligence.

As an ever-expanding technology, the full potential of artificial intelligence has not been fully realized. “New applications will create fundamental and sometimes difficult changes in workflows, roles, and culture, which leaders will need to shepherd their organizations through carefully.”[11] Companies that are committed to breaking down organizational structures through widespread collaboration, training, and planning around AI adoption will find themselves at a great advantage, as many company executives lack the understanding of the bigger picture implications of AI adoption. Those who can adapt, will lead the way in artificial intelligence adoption and influence larger changes across all industries.

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