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How AI and Algorithms are Reshaping Organizations and Transforming the Way We Work

Artificial intelligence (AI) and algorithms have rapidly advanced over the past decade and are now infiltrating nearly every aspect of our lives and transforming entire industries. Once limited to science fiction stories, AI is increasingly woven into the fabric of our daily existence through applications ranging from internet search and social media to transportation, education, healthcare, retail, and more. This unprecedented technological transformation brings with it both tremendous opportunities and distinct challenges for organizations and their leaders.


Today we will explore how AI and algorithms are reshaping organizations and fundamentally changing the nature of work and how leaders can navigate this AI revolution and promote an adaptive, learning culture that capitalizes on the benefits of emerging technologies while mitigating potential downsides.


Defining AI and Its Principal Technologies

Before delving into AI's wide-ranging impacts, it is important to establish a common understanding of exactly what AI entails. At its core, AI refers to the ability of machines to mimic human intelligence processes like learning, reasoning, and problem-solving (Russell & Norvig, 2020). A variety of specific AI technologies have emerged that enable increasingly sophisticated machine behavior:


  • Machine learning: The ability of algorithms and statistical models to perform tasks by "learning" from large amounts of data without being explicitly programmed.

  • Deep learning: A subset of machine learning using artificial neural networks modeled after the human brain that can analyze unstructured data like images, video, and speech.

  • Natural language processing (NLP): The ability of machines to understand, interpret, and generate human language.

  • Computer vision: Systems that can identify and analyze visual imagery to perform tasks like facial recognition, object detection, and image classification.

  • Decision analytics: Using historical data and algorithms to help organizations improve decision-making across various business functions.

  • Robotic process automation (RPA): Software robots that emulate human actions by executing repetitive, rule-based tasks at high speeds and scale.


These technologies together comprise AI's foundational toolkit and are rapidly changing how we live and work.


Industry Disruption and Work Transformation

Gartner estimates that AI technologies will create 2.3 million new jobs in 2020 while eliminating 1.8 million existing ones as automation accelerates across entire sectors (Gartner, 2019). Some of the most visible AI impacts are transforming both blue-collar and white-collar work.


  • Healthcare: AI aids medical diagnosis, reducing diagnostic errors. Hospitals leverage robotics and automated systems to tackle repetitive tasks like medicine dispensing, transporting items, and sterilizing medical equipment (Gomes, 2019).

  • Transportation: Self-driving vehicles powered by computer vision, deep learning and other AI are poised to reshape the trillion-dollar transportation industry. Ride-sharing services employ AI to optimize vehicle routing and dispatching (Sherman, 2019).

  • Manufacturing: Intelligent robots are rapidly automating industrial processes like welding, assembly and quality inspection using computer vision, machine learning and robotic manipulation (Vigoda, 2019).

  • Finance: AI powers robo-advisors that provide automated investment portfolios based on algorithms. Computer vision reviews documents for regulatory compliance. Machine learning detects fraud and money laundering patterns in financial transactions (Martin, 2016).

  • Retail: AI improves product recommendations, optimizes inventory, and detects anomalies in sales data. Computer vision powers smart checkout lanes, inventory robots, and loss prevention (Knight, 2017).


While some jobs become obsolete, AI and automated processes create new kinds of roles for human workers centered around problem-solving, creativity, management, and collaboration alongside machines. Yet AI is undoubtedly transforming core job functions as algorithms increasingly take over routine physical and cognitive tasks. This disruption necessitates constant skill adaptation across all industries and roles.


Reskilling the Workforce for an AI Future

As advanced technologies like AI become infused throughout organizations, the skills required of workers are rapidly shifting. Roles focused on physical labor or routine information processing face increasing commoditization and risk of automation, while jobs centered around human skills like reasoning, creativity, social-emotional intelligence are less susceptible to replacement by machines (Manyika et al., 2017). Sustaining competitive advantage in the AI era demands a redesigned workforce development strategy focused on continuous reskilling and lifelong learning.


Some key actions required of leaders include:


  • Assessing skill needs: Analyze which roles are most exposed to automation and identify new skill categories like data literacy, algorithm management, and human-AI collaboration that will be crucial.

  • Developing reskilling programs: Launch targeted reskilling programs through workshops, online courses and on-the-job experiences to help workers gain AI/digital skills or transition to new functions less prone to automation.

  • Facilitating self-directed learning: Foster an adaptive, learning culture where employees proactively upgrade skills through ubiquitous access to online learning resources, mentors, and developmental work assignments.

  • Rethinking performance management: Tie performance ratings less to functional tasks and more to human skills, self-directed learning, and adaptability for the future.

  • Managing talent differently: Use AI to help identify top performers with desired AI/digital acumen. Strategically deploy talent and form teams leveraging human-AI synergies.

  • Educating leaders: Develop AI leadership programs so managers understand technology impacts and how to optimally integrate humans and AI together.


Effectively reskilling the workforce will be critical for organizations to capture the opportunities posed by AI-driven change while protecting jobs from automation threats. An emphasis on cultivating human skills, lifelong learning mindsets, and fluid talent deployment can help maintain a competitive human capital advantage.


Leadership Strategies for Navigating the AI Revolution

Navigating the AI revolution presents profound leadership challenges but also opportunities for organizations that thoughtfully guide this technological transition. Leaders play an instrumental role in setting the right cultural foundations and strategic approaches to maximize AI's benefits. Some effective leadership tactics include:


  • Establish an AI vision and strategy: Clearly articulate how AI specifically enables key business objectives and competitive differentiation. Communicate the vision across all levels.

  • Instill experimentation and risk-taking: Foster an environment where employees feel empowered to experiment with AI applications, new tools and technologies without fear of failure. Learn rapidly from both successes and failures.

  • Focus on augmenting humans: Frame AI adoption as augmenting and amplifying human capabilities, not replacing people. Highlight how workers complement AI's strengths.

  • Build multidisciplinary teams: Form collaborative teams comprising data scientists, engineers, and domain experts from each functional area to cocreate AI solutions aligned to business needs.

  • Upskill leaders first: Prioritize helping managers understand AI fundamentals and techniques for integrating emerging technologies responsibly and ethically within their teams.

  • Continuously evolve culture: Shape and reinforce desired cultural traits like transparency, adaptability, curiosity and collaborative problem-solving crucial for harnessing AI over the long-run.

  • Institutionalize governance practices: Establish clear policies and oversight mechanisms managing AI model performance, data privacy/security, algorithmic accountability, mitigating unintended biases, and addressing other ethical risks proactively.


Leaders who adopt such bold yet prudent strategies will be best positioned to drive organizational transformation through AI, empower their people, and unlock new sources of customer value—thereby gaining a sustainable competitive edge. Continually adapting leadership approaches and company culture will be vital to realize AI's immense possibilities.


Conclusion

AI and advanced algorithms are profoundly disrupting entire industries and changing the nature of work in unprecedented ways. While threats like job automation persist, AI also provides unparalleled opportunities for augmenting human expertise, boosting productivity, fueling innovation, and raising societal living standards if implemented judiciously. Navigating this revolution demands that organizations thoughtfully develop people and skills, shape cultures, and apply technology in ways that maximize collaborative human-AI synergies. Leaders play a pivotal role guiding strategic AI adoption, cultivating curiosity and experimentation, and championing ethical practices that sustain competitive advantage through these disruptive times of technological change. Those who rise to the challenge stand to transform their enterprises and communities through harnessing AI’s immense potential for the betterment of all.


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Jonathan H. Westover, PhD is Chief Academic & Learning Officer (HCI Academy); Chair/Professor, Organizational Leadership (UVU); OD Consultant (Human Capital Innovations). Read Jonathan Westover's executive profile here.



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