Check out all the on-demand sessions from the Intelligent Security Summit here.


For many companies, artificial intellitence (AI) is poised to go beyond the hype and deliver actual business value. According to the 2022 NewVantage Partners executive survey, nine out of 10 Fortune 1000 companies are investing in AI. Yet only 26% of the survey respondents have been able to deploy it at scale. 

The majority identified culture — organizational alignment, business processes, change management, communication, “people” skill sets and resistance or lack of understanding to enable change — as the biggest impediment to widespread AI adoption.

The symbiotic relationship between culture and technology

Most business leaders acknowledge that culture is important, but they often struggle to define what it is, much less how it can be altered to survive in an ever-changing digital environment.

The term may be ill-defined, but culture makes your company what it is. Think of culture as a collection of values, expectations and practices that guide and inform the actions of all team members. 

Event

Intelligent Security Summit On-Demand

Learn the critical role of AI & ML in cybersecurity and industry specific case studies. Watch on-demand sessions today.

Watch Here

“Culture eats strategy for breakfast,” said Peter Drucker. Drucker’s remark captures the truth that change is never simple — and becomes outright impossible when your culture rejects or is not well-suited to drive innovation and change.

“If your organization is not ready to embrace the change, no AI project is going to succeed,” said Abhishek Rungta, founder and CEO of digital transformation solutions provider Indus Net Technologies. “Why do certain companies have exponential growth whereas some struggle even to maintain theirs? One of the major reasons is the people and the culture they are in.” 

A 2020 McKinsey Global Survey showed that only organizations with the right balance of talent, technology, strategy and a culture that encourages experimentation and innovation can achieve positive outcomes through digital transformation.

Preliminary ‘shifts’ to rewire your company for AI

The first step towards looking at culture from a technology perspective — including where AI adoption is concerned — is to stop viewing HR professionals as the sole stewards of company culture, prescribing initiatives and perks to lift employees’ spirits. According to Siobhan McHale, culture change expert and author of The Insider’s Guide to Culture Change: Creating a Workplace That Delivers, Grows, and Adapts, “Culture change is more likely to succeed when line managers and HR are both taking up the appropriate roles during the transformation process.” 

Second, it’s important to understand that AI is complex, and not plug-and-play. “In any organization, AI has to align with business goals, data, people and process,” said Sudhi Ranjan, product manager and tech head of AI-powered ecommerce accelerator Assiduus Global. 

Companies need to rigorously assess their needs and priorities, then transform their business processes and adopt the right tools and technologies to enable the change. However, Ranjan said, this can be a challenge where the organizational setup to facilitate AI adoption is not well understood. AI’s core objective is to be customer- and people-centric. So cultural transformation requires a shift in focus toward using AI to aid innovation and democratizing its use across the organization. 

The biggest barrier to adoption of not just AI, but any technology, is the people. “Employees and executives alike can slow the adoption,” said Manish Narayanaswami, associate director at workflow management company Kissflow Inc. “This can be due to fear of being made redundant, lack of understanding of the benefits and what it would mean to them and their function, and lack of quick access to the technology and its training. There is also anxiety involved in terms of change and adopting new technologies.” 

So organizations must focus on sensitizing all stakeholders, including senior executives, with the right information and training. Manish said that this will in turn set the right mindset, expectation and culture to adopt the technology together, not in silos. A company might, for example, identify which team is culturally most attuned to experiment with, adopt and scale AI pilots. This group can then lead and evangelize to accelerate adoption among other teams.

AI adoption from a cultural perspective

Enterprises implementing AI should start small and take it step by step, rather than force enterprise-wide adoption. When possible, they should start with parallel execution (implementing an AI solution along with an existing method) or a champion/challenger approach on a selected subprocess; and measure gains in terms of accepted metrics like efficiency, accuracy, profitability and scalability. 

“Any strategy around AI will need to be iterative and agile, given the rapid pace at which the AI technology is strengthening and the fact that the adoption of AI at scale is still in infancy for many organizations,” Ajay Agarwal, senior vice president and head of CoE — AI/Analytics, Happiest Minds Technologies, told VentureBeat.

Next, AI-related rollouts must go beyond being an “IT effort.” Though IT teams will understand how the rollout can benefit the business, they may not understand stakeholders’ pain points around the new tech. That’s why it’s crucial to develop a culture where IT, business and all stakeholders can work together to solve the business’s challenges. 

Tejamoy Ghosh, head of data science and AI at AI-based fintech company Aye Finance, advises companies to adopt a phased and graded implementation strategy when deploying AI to avoid major negative disruptions. Once positive impact has been demonstrated, leaders and users alike are more likely to adopt AI and actively participate in its expansion.

It’s important to understand that adopting AI cannot happen in days, weeks or months; it’s a long-term commitment and requires periodic investment to stay up-to-date. “A cultural shift imbibing openness to learning new technology and upskilling for using AI in improving operational efficiency becomes necessary to move the needle forward towards a wider organizational AI adoption,” said Kushal Prakash, co-founder of AI-based fintech company PoddL. 

Developing a culture that’s ready for AI

Requirements for AI initiatives will vary depending on the use case and organization. In some cases it may make more sense to use external services, while others may need to be run internally. But whatever the situation, it’s crucial to be honest about your readiness. Julian Sewell, business development representative at applied AI service and solutions provider Faktion, highlights six important elements to consider when building your AI culture:

  1. Value data and analytics: Companies should focus on building a centralized data technology infrastructure and team. This team should be able to develop a data strategy and ensure that the right data is collected the right way. They also need to pay close attention to the analysis of the data to ensure positive outcomes. 
  1. Decision-making: Companies should demonstrate true leadership through vision, action and budget. They must foster a sense of ownership among key leaders before undertaking any AI initiatives.
  1. AI-strategy framework: Business leaders should understand why they are adopting AI in the first place. They should understand the opportunity size, investment level and strategic rationale. Companies need to figure out how they are going to adopt AI: Will the tools be off-the-shelf or custom-made? Will they be built internally or purchased from vetted vendors? What are the regulatory requirements? Also crucial is a timeline to ease integration while evaluating risks.
  1. Pick the right use cases: Companies must first determine whether a problem is solvable and suitable for AI. They should understand how to measure success and whether there is a clear ROI.
  1. Educate stakeholders: Stakeholders must understand the overall impact, limitations and potential of AI implementation. The team must consist of AI experts who have both theoretical and hands-on practical experience. 
  1. Learn, improve and iterate: Companies should identify the key elements of thought and action that can produce the desired outcome, and how these can be carried forward into the future. 

There’s a high probability that an AI effort will fail if the company ignores cultural change. If every person in the company is not comfortable using the technology, no magic wand will harvest a positive outcome. So it’s essential to create a culture that welcomes AI adoption before implementing any AI-based solution.

VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.