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Prepare for AI with Change Management

Learning Objectives

After completing this unit, you’ll be able to:

  • Identify how AI has impacted various industries.
  • Explain the evolution of AI.
  • Summarize the challenges businesses face when implementing AI.

The AI Evolution

Artificial intelligence (AI) is evolving at breakneck speed, creating unprecedented opportunities and challenges across every industry and function.

  • Healthcare: AI-powered diagnostic tools, personalized treatment plans, and predictive analytics to anticipate disease outbreaks
  • Finance: Fraud detection, algorithmic trading, credit scoring, and personalized financial advice
  • Retail: Personalized shopping experiences, inventory management, and customer service chatbots
  • Manufacturing: Predictive maintenance, quality control through computer vision, and supply chain optimization
  • Automotive: Autonomous vehicles, driver assistance systems, and predictive maintenance
  • Marketing: Customer behavior analysis, targeted advertising, and content generation
  • Human resources: AI-driven recruitment, employee engagement analytics, and workforce management

These are a small representation of what’s available with the evolution of AI. The success of AI in the business world relies on choosing the right solution and on ensuring deployment goes smoothly.

Salesforce has a long history of helping customers transform with AI.

  • Wave 1: Salesforce started ‌the first wave, predictive AI, with Salesforce Einstein. We knew in 2014 that AI was going to change customer relationships and we established an in-house research team that helped pioneer AI for CRM with the launch of Einstein. This provided amazing results for our customers to sell smarter, serve smarter, and engage smarter.
  • Wave 2: Generative AI brought about the release of our GPT products, producing incredible productivity and a range of new capabilities like deal insights, account summaries, and briefings.
  • Wave 3: We’re rapidly entering a new wave of AI where autonomous agents communicate with each other and do tasks for you. Today, Agentforce for Sales can craft a follow-up sales email based on previous communications and account activity. And Agentforce for Service allows service agents to use AI-generated contextual responses when chatting with a customer.

Challenges to Successful Implementation

Machines capable of making complex decisions once only dreamed up in science fiction books are now a reality, and every business wants to capitalize on this opportunity to increase growth, productivity, and customer success.

However, over 70% of all AI transformations are falling short of expectations, with people challenges being the primary barrier they're unable to overcome.

These are the top five people-related challenges businesses face when implementing AI.

  1. Resistance to change: AI adoption often faces pushback from employees who fear job displacement or disruption to established processes.
  2. Skill gaps and workforce readiness: AI implementation necessitates reskilling employees to work alongside advanced technologies. Many organizations face challenges in upskilling or retraining their workforce, especially in areas like data analysis, AI operations, and machine learning.
  3. Ethical and bias concerns: As AI systems, particularly generative AI, are increasingly being used for decision-making, employees are concerned about the ethical implications. AI can inherit biases from training data, which can lead to unfair or harmful outcomes.
  4. Trust and transparency: The “black box” nature of AI can create distrust among employees and stakeholders. Without clear understanding or transparency on how AI models work, especially in generating decisions or content, many employees resist relying on AI systems.
  5. Cultural alignment: AI adoption often requires a shift in organizational culture toward embracing data-driven decision-making and automation. However, fostering this mindset can be difficult, particularly in companies with traditional operational practices.

Failing to address the people side of AI transformations creates a significant gap between vision and value realization, which can lead to:

  • Business and IT misalignment
  • Delayed decision-making
  • Resistance, lack of trust, anxiety, and fear of failure
  • Low productivity, adoption, and suboptimal use of tools
  • Reverting to old ways of thinking and working
  • Attrition due to degradation of the employee experience

By proactively addressing the people side of the AI transformation through the implementation of a tailored change management strategy, ethical frameworks, and strong leadership, customers can successfully shift to new ways of working, increase speed to value, and result in achieving the defined business outcomes.

If only there were a framework to help with AI change management… oh wait, there is! Continue to the next unit to learn how to pull all the right LEVERS to successfully implement AI change.

Resources

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